Image Retrieval

Author

Steven Ndung’u et al.

Published

June 24, 2024


Model Evaluation COSFIRE Filters Approach


Introduction

We obtain the 26 statistically significant sets of hyperparameters from the classification paper along with their respective training, validation, and test descriptors. Based on these descriptors, we perform image hashing for each set of descriptors using a selected set of MLP hyperparameters (for the grid search).

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The outputs below represent an example of a single experiment based on an array of hyperparameters considered to determine the optimal configuration of the MLP hashing architecture (For bit size 32).

Code
class CosfireNet(nn.Module):
    def __init__(self, input_size, bitsize, l1_reg, l2_reg):
        super(CosfireNet, self).__init__()
        self.l1_reg = l1_reg
        self.l2_reg = l2_reg
        self.hd = nn.Sequential(
            nn.Linear(input_size, 300),
            nn.BatchNorm1d(300),
            nn.Tanh(),
            nn.Linear(300, 200),
            nn.BatchNorm1d(200),
            nn.Tanh(),
            nn.Linear(200, bitsize),
            nn.Tanh()
        )
    def forward(self, x):
        regularization_loss = 0.0
        for param in self.hd.parameters():
            regularization_loss += torch.sum(torch.abs(param)) * self.l1_reg  # L1 regularization
            regularization_loss += torch.sum(param ** 2) * self.l2_reg  # L2 regularization
        return self.hd(x), regularization_loss

Without regularization

With regularization
Tip

tiply, each row represents a unique combination of MLP hyperparameters, and every column represents the results yielded by each of the 26 statistically significant sets of descriptors.


The results in this presentation are from two experimental designs:

The thresholding is based on fixed values between -1 and 1 on a step size of 0.1.

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
32 372 32 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 84.82 84.18 86.02 87.69 86.39 84.73 84.65 84.76 86.96 85.58 88.88 86.20 87.22 86.42 86.48 86.12 88.42 87.77 87.82 87.82 86.04 88.28 89.25 88.18 88.50
35 372 32 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 84.90 85.24 86.55 85.68 85.95 86.51 86.51 86.33 87.11 85.56 91.15 87.50 85.41 84.28 87.03 87.76 88.19 43.72 88.81 87.18 89.50 87.07 86.97 89.97 88.74
44 372 32 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 86.76 85.87 85.50 85.82 83.94 86.14 86.52 89.03 85.61 85.36 87.82 90.21 85.75 85.88 87.95 86.97 86.65 87.33 88.36 88.13 90.42 89.06 89.74 87.95 89.29
47 372 32 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 85.97 86.44 85.33 86.07 84.88 90.44 84.60 86.48 86.09 85.96 88.27 85.81 85.60 86.64 87.72 86.41 87.40 87.95 91.31 86.88 88.47 88.21 85.73 88.74 87.80
96 372 32 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 85.16 87.37 85.56 85.29 86.22 87.62 43.72 88.58 86.88 87.46 89.44 89.36 86.51 89.21 88.57 43.72 86.57 86.87 89.81 88.68 89.04 89.26 89.90 87.64 87.94
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.47 87.08 84.36 86.55 86.57 88.08 87.45 86.88 87.08 86.79 89.07 88.21 86.33 85.30 88.03 86.91 86.80 87.80 89.13 89.74 90.60 89.02 89.72 88.91 89.06
108 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 87.26 86.15 86.98 86.80 87.01 87.63 85.50 86.17 89.16 88.01 88.29 88.50 89.30 86.56 86.96 86.63 86.66 88.81 88.92 88.35 88.92 87.39 87.13 89.87 90.30
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.54 84.88 87.87 86.70 88.55 87.58 87.46 86.24 89.87 88.57 88.20 89.83 89.44 87.26 87.25 86.37 87.98 89.71 87.20 87.60 90.87 86.13 88.69 88.61 89.97
160 372 32 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 86.56 86.59 84.36 85.05 85.06 87.18 84.31 86.53 86.10 85.81 87.21 86.98 86.43 88.40 85.53 79.54 86.77 83.67 88.46 90.74 87.18 88.19 85.79 88.13 88.95
163 372 32 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 85.67 86.79 85.62 85.62 78.36 86.72 85.32 87.70 88.29 87.67 87.96 88.81 87.34 87.92 87.65 85.05 86.15 86.02 89.07 87.85 90.72 87.21 87.75 88.53 90.09
172 372 32 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 85.62 85.72 85.73 86.86 87.20 88.11 87.12 43.72 87.47 87.40 86.28 85.85 86.90 43.72 84.75 88.26 86.92 86.24 89.14 87.61 86.79 87.68 43.72 89.47 86.80
175 372 32 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 83.57 88.60 85.05 85.52 86.78 87.13 85.17 88.53 88.17 86.04 88.37 89.63 89.48 87.61 85.61 88.29 86.31 85.96 88.70 88.63 89.02 88.31 88.51 87.98 88.48
224 372 32 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 83.36 84.48 86.66 85.32 83.12 87.95 84.12 86.79 85.56 87.03 88.05 88.96 85.31 87.24 86.86 87.64 87.18 86.00 88.02 88.37 88.45 88.11 88.62 87.30 88.42
227 372 32 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 86.99 85.76 86.61 87.65 84.57 88.23 86.23 86.47 85.24 85.36 87.21 87.18 86.06 86.31 90.00 87.54 85.60 86.79 89.20 87.90 86.25 86.35 87.34 87.82 87.58
236 372 32 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 87.58 85.74 85.88 84.22 86.54 86.54 84.84 86.50 87.28 84.06 88.49 86.94 85.86 88.56 85.99 85.66 85.20 86.38 88.42 88.66 90.69 89.64 88.39 89.91 88.02
239 372 32 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 85.45 85.46 85.71 85.32 87.23 86.94 83.33 84.72 83.99 86.25 87.65 91.67 86.32 86.19 86.33 87.86 86.93 86.53 88.48 87.75 89.61 87.32 88.75 89.23 88.37
288 372 32 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.08 84.04 84.64 86.56 85.57 85.51 86.33 88.45 88.87 86.04 86.50 88.38 85.64 87.41 85.36 86.57 43.72 84.89 43.72 86.61 89.37 86.93 88.91 88.72 88.58
291 372 32 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 85.00 86.97 86.65 84.47 85.31 85.82 84.76 85.96 87.66 86.00 88.10 87.31 89.02 86.31 87.95 87.97 87.17 85.71 86.50 87.66 88.93 88.68 88.41 89.42 88.33
300 372 32 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 86.72 86.78 86.36 83.74 86.64 86.59 86.55 89.40 85.25 85.59 87.28 87.35 88.22 84.84 86.27 87.74 87.33 86.02 89.33 88.86 88.11 88.47 43.72 87.66 88.78
303 372 32 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 85.54 86.12 86.83 83.76 86.98 88.87 86.10 87.55 86.42 87.73 88.23 87.69 87.35 87.17 87.09 86.53 89.32 87.56 88.39 87.90 88.17 88.37 89.39 89.73 88.95
352 372 32 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 86.03 83.61 85.70 84.49 86.15 86.73 81.77 87.36 84.25 87.67 87.49 88.12 87.50 88.50 87.18 87.63 86.02 87.43 86.91 88.82 90.44 87.79 87.34 88.32 88.13
355 372 32 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 85.13 84.65 85.42 84.80 86.61 86.87 87.04 86.11 87.08 87.83 86.10 87.46 86.46 85.79 85.52 87.59 86.48 88.20 87.28 88.50 88.31 87.58 89.13 87.14 88.39
364 372 32 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 85.80 88.79 86.03 85.09 87.04 86.27 86.72 88.49 86.59 88.62 87.48 87.42 85.72 86.16 89.33 86.84 88.79 87.24 88.92 88.41 89.00 90.10 88.34 81.52 88.05
367 372 32 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 86.33 86.86 85.78 89.31 86.21 86.75 85.48 87.72 88.56 86.51 88.42 86.85 88.53 85.72 86.97 87.22 86.84 87.01 89.00 87.50 90.23 88.81 87.17 88.96 87.41
416 372 32 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 85.49 85.61 84.93 83.02 85.13 86.70 85.27 86.69 85.87 88.67 85.30 85.72 88.21 88.16 85.26 87.84 88.21 87.60 87.98 91.87 87.00 88.63 83.66 87.36 89.35
419 372 32 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.68 84.95 85.68 85.89 84.71 87.03 85.49 87.81 86.72 86.87 87.43 86.22 87.80 86.80 89.21 88.01 86.27 87.33 88.55 87.40 89.01 88.94 90.13 87.91 90.18
428 372 32 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 86.25 89.25 85.15 85.93 86.30 88.74 85.50 86.49 84.94 88.25 88.57 86.75 87.91 87.10 87.20 87.53 87.98 86.24 89.57 88.24 89.71 89.51 89.01 89.81 86.96
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 85.72 85.81 86.24 87.63 84.94 87.47 84.27 85.81 85.83 87.51 88.27 89.92 87.52 85.80 86.03 86.76 90.59 85.74 89.70 87.99 90.48 88.20 43.72 87.94 89.55
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 86.47 85.23 87.09 86.92 86.11 86.22 84.78 86.88 86.61 87.75 89.84 89.06 86.93 85.81 87.06 87.97 85.70 88.13 89.07 90.33 87.81 92.61 89.41 88.31 89.96
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 85.50 86.98 87.25 87.08 87.69 90.44 83.91 86.28 43.72 87.61 89.66 89.77 86.61 87.63 88.08 87.40 85.53 87.68 90.02 88.12 90.87 88.35 88.06 87.03 89.98
492 372 32 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 84.68 87.15 85.57 86.77 84.22 84.87 85.11 84.73 86.45 85.94 87.13 90.41 86.84 87.28 86.95 87.59 88.94 88.76 88.10 88.11 89.78 88.54 89.73 88.95 88.92
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.53 86.15 85.32 86.37 83.24 89.48 90.21 88.14 87.93 88.02 86.47 89.64 90.62 86.92 91.48 87.75 87.88 87.74 88.88 91.25 89.24 88.83 90.97 87.81 89.87
544 372 32 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 85.76 84.85 84.82 85.11 85.59 87.20 83.61 85.53 86.67 86.07 86.43 86.58 88.60 85.22 86.17 88.42 83.21 88.30 92.44 89.44 89.65 90.33 86.70 88.24 88.53
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 86.14 87.67 86.50 87.07 87.51 89.98 88.49 87.38 87.17 89.53 88.39 89.59 88.90 88.02 86.27 90.24 85.71 85.20 92.18 90.23 88.57 88.39 89.98 91.55 91.02
556 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 86.12 85.43 85.71 84.21 87.99 87.76 87.30 86.55 85.79 91.00 88.08 91.82 87.31 87.38 87.00 87.10 85.69 85.60 91.76 87.93 87.94 89.74 87.72 88.83 87.69
559 372 32 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 86.31 84.13 87.22 86.30 84.36 87.74 84.61 88.01 84.98 83.68 89.35 87.28 87.40 85.55 89.60 87.13 85.28 86.15 89.74 90.44 89.05 89.19 88.67 89.10 89.08
608 372 32 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 83.56 85.05 84.51 84.14 83.06 84.78 43.72 88.35 84.77 86.44 86.46 87.10 87.14 86.39 88.34 86.03 88.50 84.93 87.14 87.30 87.56 89.50 88.01 87.96 88.57
611 372 32 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 86.30 83.19 87.16 85.69 86.07 87.37 84.27 86.98 86.55 85.25 88.60 88.79 88.60 86.71 85.79 86.28 85.25 86.80 87.61 87.08 88.66 88.52 88.66 87.06 86.33
620 372 32 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.41 86.57 89.00 86.02 86.98 86.27 84.91 89.05 86.48 84.41 88.09 87.51 86.30 88.63 87.98 89.22 89.58 85.59 87.09 87.54 88.43 88.62 88.15 87.59 88.30
623 372 32 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 88.05 89.92 87.67 85.70 84.82 89.30 85.10 87.01 84.68 84.75 87.70 87.86 87.95 86.42 87.63 86.06 87.76 86.57 89.51 88.64 87.99 87.60 89.93 88.38 89.91
672 372 32 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 84.19 86.51 84.81 83.88 83.99 86.38 84.72 88.25 86.49 87.05 87.72 86.75 85.36 84.18 85.58 84.68 86.42 87.61 87.87 87.91 86.93 88.39 87.59 87.68 88.54
675 372 32 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 85.58 88.65 86.20 84.19 86.13 85.73 88.32 86.90 85.61 87.57 87.88 87.32 87.60 84.88 89.33 86.09 87.18 86.15 88.50 88.65 90.27 89.16 88.68 88.64 88.11
684 372 32 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.92 89.19 87.23 84.40 88.17 87.19 85.58 87.34 88.59 87.05 87.24 87.37 86.22 87.59 86.62 87.73 86.14 86.17 86.36 85.31 92.94 88.86 89.37 88.20 89.56
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 86.32 86.76 87.05 87.52 86.74 87.02 86.38 87.31 88.17 86.68 88.64 89.54 87.36 87.10 87.99 88.63 86.43 87.45 89.60 88.46 89.09 89.80 90.05 88.30 88.81
736 372 32 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 85.45 53.61 86.22 87.30 82.06 88.01 84.20 86.60 87.63 88.56 86.51 87.82 87.78 89.33 85.02 88.07 84.12 87.17 86.61 89.09 88.40 90.18 89.80 87.89 88.09
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 86.19 86.57 85.85 88.08 43.72 87.68 86.76 86.56 88.23 87.70 87.34 87.72 86.60 87.38 85.76 86.87 84.97 88.22 85.92 88.71 89.70 88.69 88.98 87.98 89.65
748 372 32 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 86.27 86.75 83.40 87.06 85.29 86.34 85.07 85.44 84.63 86.51 87.03 88.49 85.14 85.94 87.76 88.26 86.22 86.30 88.27 89.87 87.24 89.37 88.79 89.85 87.22
751 372 32 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 86.03 87.19 85.04 87.37 85.30 86.19 87.39 86.97 87.99 85.46 88.67 87.80 87.65 89.27 87.83 86.93 88.18 85.63 87.36 89.86 89.65 88.81 88.68 89.74 87.55
800 372 32 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 87.08 86.50 85.41 89.72 88.55 85.22 84.77 84.99 84.52 86.69 85.35 88.74 87.60 87.41 87.10 87.14 85.50 87.37 90.44 87.82 88.45 88.60 88.80 87.08 87.95
803 372 32 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 85.15 86.45 85.77 85.74 86.61 87.55 85.42 85.27 85.34 85.40 87.80 88.06 87.54 84.11 87.05 86.91 86.82 88.70 88.07 89.00 89.24 86.55 88.26 87.78 88.21
812 372 32 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 85.39 87.11 85.75 89.81 85.89 86.89 83.76 87.52 87.41 87.22 87.48 88.49 85.35 87.29 85.68 86.41 86.29 86.63 88.06 88.86 88.54 86.23 88.62 89.32 86.80
815 372 32 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 84.01 86.70 85.95 87.82 85.53 85.72 84.76 85.41 86.17 86.83 87.74 88.71 87.41 87.31 86.24 87.65 84.51 86.96 88.11 88.02 88.80 87.22 87.94 87.21 88.65
864 372 32 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 84.90 86.55 85.98 85.41 86.51 86.91 85.27 86.66 43.72 87.02 87.74 89.56 86.32 87.07 86.49 87.31 86.40 85.96 88.29 88.42 88.61 88.68 85.50 88.43 89.74
867 372 32 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 86.71 87.05 87.08 87.49 86.33 85.87 85.79 86.08 87.42 84.99 90.08 88.88 85.93 87.92 87.34 86.17 88.05 87.61 89.45 86.30 89.21 89.76 90.59 89.37 87.00
876 372 32 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 87.85 90.38 86.35 85.61 85.52 87.08 85.07 86.97 87.82 85.10 87.25 86.74 85.98 87.29 87.72 89.51 85.87 86.29 86.73 89.50 90.30 86.97 89.55 88.77 87.39
879 372 32 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 87.75 86.42 86.67 87.02 86.32 87.23 86.10 86.96 85.99 85.60 86.49 87.80 86.22 85.90 86.04 86.00 87.17 89.02 88.92 89.02 87.99 88.42 88.08 88.83 88.26
928 372 32 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 84.91 89.98 87.44 85.05 86.76 86.81 82.80 86.31 87.31 89.14 87.40 87.95 85.85 89.82 87.99 86.35 86.13 85.95 86.73 87.35 88.64 87.00 88.95 88.58 83.37
931 372 32 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 84.93 86.73 85.21 84.11 86.37 87.94 85.40 84.53 87.10 86.49 88.67 88.15 84.47 85.86 90.21 88.21 86.53 87.92 86.36 89.30 88.72 90.17 89.64 65.14 89.20
940 372 32 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 83.55 87.05 87.36 86.97 85.60 87.40 85.77 86.47 84.64 84.71 88.59 87.21 88.66 87.75 86.34 87.09 85.03 86.25 87.80 87.85 87.37 88.31 87.77 89.36 88.92
943 372 32 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 86.20 87.80 84.36 87.17 86.24 86.95 85.57 87.44 87.62 85.95 87.03 86.30 87.00 86.59 87.76 86.02 86.43 88.42 88.16 88.62 88.42 88.61 89.49 81.57 88.39
992 372 32 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 84.01 87.10 85.62 83.28 85.06 85.30 85.71 85.78 89.63 86.08 89.19 88.54 87.79 87.86 84.05 87.69 88.92 86.96 89.05 88.98 89.90 89.16 89.58 89.11 83.04
995 372 32 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 86.45 84.83 85.58 85.87 88.63 85.66 86.04 86.45 86.53 85.34 87.39 90.10 86.45 88.39 88.35 86.48 87.80 85.96 87.11 88.65 88.77 85.76 87.98 89.25 87.92
1004 372 32 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 83.95 85.29 89.25 86.02 86.10 86.55 85.95 86.47 85.99 87.79 89.09 84.37 84.57 87.21 87.41 89.61 86.70 86.98 87.60 88.55 88.69 88.95 88.09 88.06 89.35
1007 372 32 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 85.85 85.54 86.20 84.69 90.07 88.63 84.52 88.73 85.73 85.04 87.24 88.04 88.20 87.47 88.51 87.74 89.30 85.58 86.75 87.91 90.04 89.65 88.57 89.55 89.47
1056 372 32 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 86.44 91.60 85.72 84.35 84.12 86.49 85.26 87.74 87.29 84.82 88.83 87.77 87.23 87.91 86.58 87.73 85.50 86.50 89.39 87.08 91.02 89.63 88.15 90.16 89.91
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 86.70 85.32 87.35 86.52 86.28 87.35 87.73 86.71 86.79 87.70 89.10 88.22 86.50 86.82 87.90 88.35 87.90 87.53 90.55 88.27 87.58 89.38 90.06 89.91 89.77
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.27 87.65 87.08 85.49 87.92 86.72 86.20 87.75 88.60 89.02 88.44 88.49 89.48 85.41 87.67 88.37 87.00 87.65 89.04 89.17 88.42 89.17 88.13 90.03 90.25
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 87.21 85.68 88.49 87.98 89.55 86.99 87.26 87.18 87.88 87.80 88.27 86.99 87.97 86.66 87.00 86.67 86.82 87.74 87.50 88.64 89.37 89.69 91.14 89.71 87.49
1120 372 32 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 86.19 86.22 85.39 83.88 88.43 88.76 87.99 88.44 86.95 87.88 90.39 87.24 87.85 85.65 87.93 86.02 87.97 84.71 87.91 90.74 88.01 89.89 88.12 89.27 87.35
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.99 85.29 87.42 87.70 85.80 90.65 86.24 88.33 86.26 86.88 87.69 88.38 88.70 87.21 88.69 86.83 87.12 88.26 88.04 88.31 89.53 90.34 90.14 89.97 89.32
1132 372 32 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 82.34 87.24 85.83 84.83 84.32 87.83 84.92 86.55 87.60 86.91 86.95 90.15 85.84 85.01 88.62 88.54 85.45 85.87 87.78 92.33 89.65 89.59 89.37 87.15 87.88
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.14 87.21 88.77 85.25 88.44 87.57 84.43 86.61 85.73 87.44 87.96 87.76 87.43 87.85 89.03 87.65 86.69 86.97 90.06 91.21 88.72 90.81 88.03 91.39 90.79
1184 372 32 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 83.84 86.94 84.75 88.37 83.90 85.93 84.25 86.79 82.74 85.74 85.81 86.50 85.84 89.04 89.22 87.42 85.56 85.56 87.57 86.29 89.14 87.84 87.81 88.19 87.76
1187 372 32 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 86.00 89.37 86.18 88.09 85.35 86.99 85.06 86.32 87.47 85.81 86.37 88.88 89.35 86.76 88.29 87.47 85.60 86.86 87.92 90.47 87.65 87.99 87.98 89.12 88.54
1196 372 32 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 85.15 83.40 83.44 83.05 87.05 87.19 83.84 85.40 85.51 86.10 88.04 87.68 89.75 87.02 88.74 86.11 87.85 87.24 88.71 90.36 87.80 89.29 88.25 89.28 90.64
1199 372 32 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 84.80 85.76 86.89 84.13 86.20 86.34 86.29 86.71 87.36 86.08 88.41 88.83 86.34 86.22 86.11 87.46 89.71 88.02 85.09 87.38 89.01 87.74 87.69 89.90 88.30
1248 372 32 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 85.11 85.26 85.55 83.69 86.62 87.52 86.49 86.53 85.96 85.14 88.01 88.12 88.55 86.44 86.22 87.02 84.47 86.57 90.54 88.03 90.00 88.30 87.97 86.99 88.08
1251 372 32 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 86.01 86.78 87.23 86.34 86.63 87.94 86.29 85.97 86.33 86.17 88.84 88.72 85.37 87.61 87.65 85.93 86.55 87.98 88.98 88.80 91.31 87.95 88.41 89.36 88.74
1260 372 32 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 87.12 86.38 87.67 86.26 85.27 86.80 85.87 86.35 86.74 87.21 88.09 89.14 86.12 83.98 89.72 86.13 85.83 87.81 88.80 87.80 88.11 88.26 89.18 88.52 88.53
1263 372 32 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 85.60 87.79 87.08 87.15 86.89 87.05 86.70 87.22 87.18 86.89 89.06 89.00 88.68 85.48 85.40 86.77 87.58 87.40 88.42 88.09 88.68 90.52 87.08 89.88 89.30
1312 372 32 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 83.95 84.79 85.96 85.60 87.36 85.49 87.68 88.85 85.46 85.94 86.29 87.66 86.65 86.65 87.61 88.11 87.56 86.09 89.18 90.21 88.59 74.49 85.34 89.24 89.14
1315 372 32 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 85.10 86.25 86.59 85.16 86.37 88.25 86.80 86.56 86.48 87.55 86.90 87.82 85.54 87.53 86.17 87.03 87.73 87.36 86.79 89.25 89.96 88.94 88.99 89.88 87.74
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 85.43 88.18 88.08 86.56 84.62 87.21 86.19 86.31 87.31 88.32 88.56 87.75 87.61 89.22 87.36 89.85 85.79 87.26 89.76 89.20 88.95 87.80 89.53 87.47 88.24
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 85.33 86.79 86.24 86.12 85.69 87.93 86.82 87.54 85.88 90.08 88.42 87.90 88.21 87.53 86.26 87.62 88.40 87.56 87.86 88.68 89.91 89.05 88.02 86.67 91.92
1376 372 32 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 85.67 85.55 88.37 85.01 85.72 88.14 84.23 87.33 87.23 88.23 87.23 88.04 86.58 86.07 87.16 86.80 87.63 85.43 85.47 86.70 87.77 86.88 87.90 89.19 86.81
1379 372 32 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 84.02 86.02 87.68 84.08 85.62 85.31 85.37 86.03 83.72 85.43 88.22 90.89 86.33 88.47 84.94 88.80 85.11 87.52 87.80 89.15 87.03 87.15 85.12 88.63 88.14
1388 372 32 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 86.26 85.60 86.93 85.47 87.53 85.92 84.45 86.99 85.88 87.05 88.57 87.43 85.84 87.64 88.23 88.65 87.94 85.40 89.85 87.77 88.61 89.57 86.54 87.54 88.12
1391 372 32 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 85.31 88.10 85.53 85.69 84.48 85.40 84.22 87.88 84.17 87.13 87.54 87.11 88.34 87.67 87.13 87.69 85.81 86.39 90.01 88.13 87.71 89.36 88.86 88.34 87.51
1440 372 32 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 85.74 89.00 84.99 87.18 87.64 85.68 85.53 86.66 89.39 85.32 87.16 87.30 86.87 86.75 86.12 87.96 87.94 88.07 86.92 87.06 89.07 89.08 89.24 88.71 87.60
1443 372 32 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 87.69 87.20 87.25 86.39 85.08 84.80 86.32 85.42 87.29 85.47 87.25 86.65 87.17 85.68 87.45 86.57 87.04 86.76 88.67 86.79 87.24 87.02 88.44 88.21 88.64
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 85.93 86.79 87.17 86.05 84.99 87.28 85.76 86.04 87.79 88.24 89.22 87.85 87.40 87.91 85.73 89.09 88.92 87.09 87.44 89.69 91.22 88.93 88.92 88.60 89.20
1455 372 32 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.28 85.07 83.86 86.64 86.86 86.90 84.81 85.53 86.06 85.27 87.40 86.40 84.50 86.17 88.10 85.53 86.45 87.43 87.58 87.26 89.16 88.41 88.83 89.45 87.35
1504 372 32 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 84.98 84.18 90.51 86.11 83.88 87.26 86.81 89.47 87.15 84.02 87.26 88.78 86.17 86.40 86.28 84.85 88.34 86.16 87.97 86.65 87.32 89.41 89.05 82.34 88.30
1507 372 32 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 86.18 85.81 85.81 87.76 86.67 87.76 87.18 86.30 86.95 86.07 86.48 87.71 85.90 84.95 85.01 88.35 86.49 85.13 88.53 87.16 87.30 87.66 88.88 88.21 88.21
1516 372 32 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 84.56 86.61 86.65 85.44 84.89 88.21 85.05 89.36 85.87 85.14 86.68 87.08 87.68 84.73 85.34 87.30 86.52 86.05 87.77 88.62 88.75 88.95 86.24 88.71 88.61
1519 372 32 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 84.89 86.92 86.22 85.85 84.23 86.41 85.14 86.26 84.50 86.37 85.86 88.68 86.94 86.15 86.56 86.02 89.14 85.72 87.10 86.86 87.10 88.19 87.52 88.16 85.87
1568 372 32 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 86.31 85.86 86.38 84.48 84.33 84.53 84.91 86.70 86.66 88.59 87.14 88.18 87.80 85.96 85.44 88.68 84.56 86.80 88.23 89.66 89.60 89.25 88.01 87.99 88.86
1571 372 32 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 83.94 84.79 84.52 83.52 85.05 86.92 84.49 88.46 85.24 83.93 88.83 85.33 86.51 85.61 89.61 85.73 85.59 84.23 90.25 86.83 87.67 89.47 87.25 87.59 88.16


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
32 372 32 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 92.54 92.20 92.36 92.59 91.25 90.60 90.41 94.71 92.63 89.37 91.50 91.89 94.07 92.77 91.77 93.71 91.17 94.49 89.45 90.70 91.64 89.94 91.10 92.55 88.56
35 372 32 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 91.48 93.62 93.40 93.06 91.67 92.46 93.40 92.21 92.64 91.99 81.07 91.06 91.88 93.07 94.59 94.65 94.82 48.12 90.92 91.77 92.03 93.83 91.55 90.67 92.81
44 372 32 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 94.07 92.34 94.47 94.25 94.30 93.83 94.04 94.34 90.80 93.44 91.47 91.52 92.20 93.70 92.41 92.62 91.95 93.50 91.34 93.69 92.13 93.64 92.59 91.44 91.95
47 372 32 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 94.35 94.65 94.17 91.67 93.91 78.74 93.63 92.97 92.93 92.58 92.10 91.74 93.20 92.28 92.43 94.31 93.65 92.01 81.53 92.00 92.53 94.37 93.19 93.77 93.32
96 372 32 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 91.77 94.88 95.31 94.48 92.46 90.85 48.12 92.95 95.06 92.90 91.82 92.63 93.34 94.32 93.66 48.12 94.78 94.09 89.87 91.08 90.58 94.28 91.36 91.41 91.68
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 96.24 94.29 93.74 93.75 93.28 91.69 94.19 93.51 93.14 94.43 90.43 92.64 94.54 93.88 94.61 95.29 94.85 95.79 93.01 91.10 91.86 92.90 94.19 92.87 93.96
108 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 91.88 93.29 95.20 94.82 94.77 93.29 94.82 93.60 93.93 93.24 91.95 91.98 93.20 96.01 94.10 92.68 96.69 93.88 90.18 91.94 91.58 90.64 93.72 92.75 91.37
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.86 94.73 95.05 93.90 92.90 92.66 93.75 96.18 94.07 94.63 92.13 94.32 95.59 94.08 94.54 94.91 91.38 93.53 91.58 91.88 92.28 91.94 92.57 89.92 92.10
160 372 32 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.59 91.73 94.25 94.77 93.60 93.11 94.56 94.06 94.28 95.18 92.19 93.14 93.09 92.83 95.03 92.02 95.37 92.43 89.67 91.23 91.11 91.70 90.17 91.37 91.36
163 372 32 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.24 95.34 94.50 92.02 89.24 93.38 92.39 95.00 93.62 95.05 93.11 92.10 94.56 96.21 94.14 92.95 93.99 93.20 92.53 91.63 84.37 91.58 92.85 94.49 92.25
172 372 32 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 93.97 92.99 94.55 96.27 94.55 93.58 93.28 48.12 95.55 96.52 94.23 93.17 94.43 48.12 95.09 94.45 94.38 92.16 90.20 94.75 92.25 94.80 48.12 93.39 91.56
175 372 32 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 94.40 92.80 93.60 94.31 94.80 92.62 94.43 94.07 94.48 93.08 93.59 90.64 95.40 94.10 92.85 93.96 96.00 94.80 92.48 91.67 91.46 92.29 93.75 92.20 93.35
224 372 32 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 91.29 92.46 91.94 92.73 94.60 91.25 94.04 92.72 92.95 93.03 90.93 91.30 93.22 93.49 91.97 93.14 90.19 91.49 88.03 88.14 93.56 93.57 90.53 91.99 90.77
227 372 32 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 93.57 93.23 93.86 93.85 94.99 91.54 92.14 95.70 94.91 94.39 94.80 93.71 93.60 95.60 92.25 91.98 94.35 93.84 93.56 91.53 94.79 95.47 94.53 93.36 93.79
236 372 32 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 92.99 94.94 91.49 95.47 94.25 89.87 89.83 92.69 93.51 90.38 92.26 90.09 92.33 93.24 93.16 93.83 91.99 93.74 91.95 91.58 92.03 91.59 92.45 91.98 92.03
239 372 32 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 92.84 92.83 94.52 93.68 91.83 91.45 94.90 91.88 93.99 94.34 93.25 92.31 93.09 94.52 94.03 93.41 93.33 92.26 92.25 92.38 91.83 93.80 92.63 93.06 91.69
288 372 32 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 95.06 93.89 92.64 94.34 94.13 91.76 93.33 94.22 92.87 94.49 92.52 91.94 94.20 95.06 93.75 94.27 48.12 92.87 48.12 92.64 93.43 93.01 93.44 93.87 91.50
291 372 32 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 92.43 95.68 93.62 95.51 94.80 92.05 94.04 94.44 94.08 93.79 92.37 93.32 94.12 94.80 94.96 93.30 94.76 95.08 91.29 94.78 94.35 94.24 92.77 90.59 93.95
300 372 32 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 95.01 94.75 95.33 93.50 95.13 91.94 95.01 92.03 93.59 93.02 93.30 93.46 95.49 94.52 95.68 93.92 95.13 93.59 91.81 93.36 94.08 90.11 48.12 92.75 93.46
303 372 32 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 95.11 93.42 94.63 94.56 93.30 92.48 94.02 95.14 93.46 94.51 92.55 91.63 94.48 93.47 95.04 95.06 95.21 95.35 94.11 92.94 93.80 91.28 92.75 93.91 90.00
352 372 32 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 93.25 94.03 93.55 93.53 95.14 93.15 94.27 92.71 93.14 94.83 93.87 93.80 94.01 95.06 94.39 94.84 93.37 94.20 93.10 92.51 91.74 92.38 92.81 92.47 93.69
355 372 32 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 93.75 94.79 94.20 94.84 95.83 92.59 93.83 93.61 94.21 95.29 93.85 93.60 93.84 93.40 93.16 95.02 94.36 95.09 94.61 92.35 91.36 93.56 91.42 92.15 93.06
364 372 32 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 94.50 93.06 93.93 92.03 94.04 91.86 94.61 92.76 94.36 94.54 93.39 93.60 94.14 93.15 91.54 96.43 91.38 94.74 93.42 91.49 92.82 91.70 91.59 92.30 89.95
367 372 32 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 94.87 92.21 94.68 94.05 94.75 91.29 94.84 93.67 94.24 94.48 91.32 93.56 93.74 94.35 93.96 95.81 94.51 94.17 94.28 93.32 92.49 93.75 94.89 93.98 92.30
416 372 32 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 94.62 90.09 93.78 87.95 93.20 90.25 92.66 90.21 94.17 93.79 89.15 94.45 94.79 94.12 89.62 95.09 91.59 93.00 94.26 92.48 92.71 92.31 89.90 90.99 92.64
419 372 32 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 95.52 89.02 92.69 96.47 94.24 87.37 94.30 91.18 94.76 94.01 94.28 91.70 93.31 94.03 93.64 95.14 95.25 93.94 93.54 91.02 92.39 92.35 62.25 94.30 95.01
428 372 32 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 92.26 94.48 94.99 93.87 92.66 93.03 93.09 89.85 94.10 92.73 89.94 90.74 93.65 93.16 92.27 94.24 91.41 93.11 92.93 92.30 95.54 94.09 90.42 92.40 93.98
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 92.90 93.86 94.48 59.15 88.49 93.59 94.04 92.28 95.47 93.85 95.55 92.81 91.96 90.15 95.32 93.98 92.67 94.88 93.97 92.24 91.80 94.38 48.12 93.50 92.70
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 92.64 92.77 95.73 93.19 92.81 92.45 94.94 93.29 95.47 94.32 93.01 93.74 95.71 92.00 95.34 95.65 92.91 94.35 90.31 87.99 91.55 59.11 92.48 85.88 90.90
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 94.09 95.24 94.05 92.62 94.14 92.15 92.12 93.46 48.12 93.82 93.25 90.46 93.82 95.88 93.75 93.98 96.53 94.37 90.92 92.84 57.77 94.20 93.51 92.66 93.37
492 372 32 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 93.94 95.61 95.27 95.52 95.56 93.01 93.61 93.35 93.12 94.22 93.19 93.69 93.12 93.70 95.25 94.24 93.76 90.84 94.29 93.61 93.22 91.78 87.80 93.49 93.08
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 93.10 96.04 92.29 92.51 88.44 94.01 94.30 94.26 93.53 95.03 94.08 93.63 91.25 94.55 92.24 95.12 94.07 93.49 92.78 92.48 92.64 93.47 91.67 93.16 93.96
544 372 32 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 93.22 93.93 95.50 91.66 92.10 93.75 92.59 94.76 94.18 93.18 92.84 94.00 90.63 92.97 92.10 91.50 91.95 93.05 91.22 93.60 91.73 93.61 94.83 93.71 94.87
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 92.16 92.18 93.59 93.63 94.31 91.73 95.74 92.59 92.72 94.42 91.45 93.78 95.29 93.21 92.47 93.78 93.16 94.60 92.95 92.26 92.80 93.70 93.84 92.30 91.30
556 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 94.48 93.32 91.89 92.43 92.27 92.55 94.13 93.21 94.53 93.09 93.99 92.52 94.53 94.82 92.99 94.64 93.65 95.26 91.49 92.66 91.99 93.32 94.62 94.43 92.69
559 372 32 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 94.03 94.21 92.87 95.00 91.92 90.50 94.40 93.53 94.88 93.08 92.90 94.50 96.31 91.87 92.16 92.79 93.68 94.78 94.02 93.26 93.73 93.68 92.93 91.95 91.38
608 372 32 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 92.55 90.78 91.84 94.34 92.79 91.71 48.12 94.31 90.56 94.18 91.23 91.48 89.85 94.21 92.20 90.83 91.21 92.87 90.40 90.63 92.01 88.41 91.38 90.38 91.91
611 372 32 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 90.60 93.50 94.14 95.84 93.36 92.39 94.74 94.19 95.18 93.96 93.31 89.50 90.58 90.31 92.60 94.41 94.77 92.73 92.72 91.33 94.64 91.13 91.24 93.39 91.75
620 372 32 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 96.26 94.04 94.91 95.30 95.27 91.79 93.64 91.93 95.29 93.93 92.41 93.74 94.28 96.23 95.19 87.22 91.45 94.88 93.47 93.29 93.18 90.06 93.03 92.83 92.52
623 372 32 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 94.48 93.21 94.10 92.85 92.10 94.58 93.26 95.42 91.01 95.70 94.04 92.54 92.92 94.92 93.84 92.91 94.44 92.26 90.67 88.42 93.11 94.42 93.17 91.62 89.06
672 372 32 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 94.65 91.19 93.54 89.44 92.91 91.59 94.35 91.13 93.30 94.52 93.46 92.62 93.22 94.31 93.57 93.46 94.13 93.97 92.91 92.99 91.75 91.85 93.14 91.12 91.99
675 372 32 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 94.15 93.78 94.18 94.43 95.08 91.62 95.05 93.82 94.67 92.47 92.96 93.17 93.69 95.72 92.17 94.08 95.08 92.81 92.89 93.36 90.40 91.44 92.90 91.82 90.63
684 372 32 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 92.38 92.93 94.06 93.43 94.26 92.75 94.45 92.50 94.17 95.70 94.87 93.88 93.06 95.45 94.20 93.44 91.71 91.63 92.77 92.51 92.35 91.54 92.82 91.30 89.67
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 91.48 93.32 93.14 93.99 94.56 91.07 94.98 93.16 90.70 91.72 94.03 93.43 93.25 94.91 91.98 93.62 93.00 92.36 91.77 92.57 92.18 92.17 92.03 93.04 91.90
736 372 32 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 93.81 93.93 92.36 91.49 93.18 93.11 92.28 94.79 93.06 94.36 92.48 93.12 94.26 94.33 91.95 94.44 93.11 93.33 90.81 91.42 90.94 91.94 92.55 93.03 92.60
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 94.13 93.08 95.22 93.19 48.12 93.79 94.52 92.88 92.19 92.60 91.04 92.06 89.44 94.77 94.66 93.70 94.76 94.09 91.44 90.47 94.16 91.96 91.75 90.94 89.82
748 372 32 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 92.74 94.24 93.46 94.97 92.51 91.79 93.58 94.91 92.96 96.04 93.92 92.15 94.29 94.91 95.29 93.27 94.19 94.54 93.80 94.11 91.32 93.27 93.80 92.00 92.40
751 372 32 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.93 92.72 93.26 94.54 93.64 93.43 93.50 91.85 93.28 93.81 94.28 91.40 93.42 91.02 93.73 95.21 94.77 91.76 93.54 91.59 91.92 90.60 91.68 91.94 92.34
800 372 32 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 92.39 93.31 91.65 91.54 93.18 89.86 93.45 94.48 93.30 95.91 92.11 90.91 90.31 93.17 92.77 91.75 93.13 90.40 90.75 89.63 89.74 93.37 92.90 94.60 94.48
803 372 32 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 94.68 95.50 93.51 95.81 93.32 91.59 93.47 94.89 93.39 92.39 92.25 93.23 92.10 93.39 91.79 93.30 94.29 93.07 90.88 86.93 90.29 91.69 92.23 93.97 94.58
812 372 32 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 93.01 92.86 94.36 93.34 92.54 92.52 93.41 95.59 93.42 95.28 91.29 92.18 90.69 93.81 94.17 93.96 96.74 93.86 92.30 93.89 93.90 93.60 93.93 93.94 94.07
815 372 32 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 90.65 91.61 93.13 93.01 92.48 91.07 92.72 93.61 91.27 91.98 91.08 91.01 92.65 92.94 92.09 92.74 93.29 90.90 92.08 87.13 91.58 92.07 91.82 93.51 89.12
864 372 32 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 93.83 94.00 93.52 94.27 93.47 92.78 93.31 91.27 48.12 93.81 92.47 93.10 93.16 94.39 92.19 94.66 94.22 94.56 91.50 89.61 90.89 91.06 92.32 91.87 91.89
867 372 32 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 92.62 94.45 93.11 94.05 92.65 91.89 95.53 95.57 93.90 94.03 91.14 92.91 93.62 93.97 92.29 92.93 93.81 94.03 92.18 93.70 93.41 90.63 92.59 91.97 91.58
876 372 32 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 94.33 91.61 94.47 94.61 95.07 93.82 93.89 95.38 92.96 94.66 94.23 92.95 93.50 93.73 91.78 93.71 95.56 95.54 91.51 93.16 90.30 93.02 91.25 92.72 93.94
879 372 32 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 94.52 94.16 95.87 93.67 95.20 93.35 92.62 93.14 93.82 94.25 91.35 93.65 94.87 93.91 95.32 95.54 95.41 95.33 91.47 91.20 92.30 95.53 92.21 93.39 92.27
928 372 32 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 93.59 92.88 94.32 93.58 93.79 92.01 96.49 93.74 95.48 95.24 93.50 93.78 93.88 94.76 93.41 94.21 96.12 95.81 91.59 92.72 92.88 92.51 92.59 91.97 94.88
931 372 32 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 94.17 95.07 95.47 93.96 95.79 93.92 93.97 94.40 93.82 93.43 93.01 92.42 93.93 93.41 91.83 94.42 94.84 93.22 92.88 90.32 92.88 92.89 92.59 91.73 91.81
940 372 32 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 93.88 94.47 93.77 95.91 95.00 93.76 93.83 93.75 94.29 94.38 93.03 95.12 95.53 93.56 93.69 93.34 93.69 95.38 92.95 93.97 91.91 91.98 93.97 94.39 90.02
943 372 32 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 94.05 94.51 94.53 95.99 95.49 92.20 92.03 92.15 94.67 94.63 93.71 94.31 93.70 94.12 92.65 93.92 94.95 94.74 94.10 93.64 93.60 91.63 92.36 92.29 93.53
992 372 32 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 95.52 91.38 59.72 84.98 65.81 92.46 92.85 93.22 93.10 94.50 95.04 93.18 91.69 94.13 90.44 94.19 89.70 93.88 92.68 92.59 94.04 93.57 91.10 93.32 78.89
995 372 32 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 91.74 89.24 89.69 95.94 93.00 91.22 94.58 94.52 92.70 92.54 92.13 92.46 95.29 91.84 93.66 93.70 92.51 95.99 92.14 91.90 91.82 93.51 91.86 91.31 94.32
1004 372 32 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 91.91 95.53 84.17 94.45 92.94 94.35 94.69 94.04 95.07 94.52 91.89 92.19 85.35 95.42 80.29 94.96 95.01 95.10 92.43 93.70 94.58 94.80 92.56 92.87 87.86
1007 372 32 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 93.93 94.41 94.33 95.44 91.93 93.22 93.99 93.48 92.77 93.71 91.67 94.62 94.25 92.74 92.15 91.52 93.72 92.32 93.40 93.09 93.67 93.05 89.94 93.65 92.47
1056 372 32 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 94.47 58.74 94.02 95.03 91.78 90.95 95.34 92.87 94.48 93.71 92.47 92.00 92.77 93.54 93.13 93.04 94.18 91.90 93.48 93.26 61.54 92.88 94.90 90.74 91.13
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.50 94.49 95.84 94.58 94.74 91.88 93.05 95.50 94.72 93.83 92.63 93.41 95.14 90.84 92.02 94.80 92.96 94.11 93.33 90.77 93.56 91.70 92.99 85.21 91.60
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 94.53 92.20 95.85 92.63 95.20 92.51 95.14 93.77 94.01 93.84 91.32 93.29 95.75 92.11 90.58 95.35 95.40 94.08 94.06 93.13 92.86 93.28 94.04 93.57 93.03
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 94.26 93.58 95.26 95.27 94.41 92.67 93.13 94.79 93.76 94.20 92.42 93.58 94.05 93.31 93.45 94.08 93.73 94.78 93.32 92.63 94.76 93.40 59.16 91.82 92.89
1120 372 32 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 93.37 93.32 94.47 94.70 92.84 92.41 94.56 93.56 94.72 95.50 90.69 93.20 95.03 95.67 93.29 92.99 92.09 90.63 93.76 90.31 87.51 94.38 94.05 92.37 91.06
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 93.62 95.56 94.62 95.98 93.28 93.15 94.36 94.21 90.55 94.30 92.83 92.95 94.24 94.32 92.92 92.19 93.76 93.30 92.21 91.82 92.93 94.06 93.71 91.27 93.49
1132 372 32 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 93.87 93.30 93.05 92.37 93.70 91.83 93.25 93.79 94.57 93.96 93.85 92.04 93.97 92.73 92.58 94.04 93.83 92.57 91.50 92.61 95.14 94.08 94.99 94.62 87.60
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 92.27 95.17 93.79 93.82 94.48 91.68 94.70 92.62 95.45 92.59 93.04 94.49 93.15 92.86 91.70 95.94 93.29 93.75 92.62 93.04 93.96 94.52 93.33 91.52 90.15
1184 372 32 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 95.69 94.11 90.79 91.02 92.72 91.26 90.71 92.36 92.53 91.32 91.64 92.02 92.74 93.87 92.20 88.79 94.06 90.80 91.68 90.69 93.56 91.23 91.62 90.13 89.42
1187 372 32 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 93.41 93.43 93.57 93.92 95.97 93.58 92.79 93.31 94.14 91.95 90.28 90.54 95.54 91.95 91.88 92.30 94.92 92.82 92.31 90.95 92.02 94.11 92.39 92.66 89.58
1196 372 32 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 92.85 93.40 94.42 93.40 92.91 91.61 94.32 94.89 93.35 93.96 94.17 90.70 93.63 95.07 93.83 91.71 93.24 92.28 93.50 92.07 92.40 95.36 94.13 92.81 93.80
1199 372 32 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 91.89 95.32 91.37 94.82 92.97 91.35 94.75 95.55 95.17 93.12 91.13 92.81 90.99 93.20 94.00 95.24 84.38 94.12 90.28 93.78 93.09 93.66 93.57 90.17 93.13
1248 372 32 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 93.12 93.59 93.72 93.64 93.23 90.07 92.64 93.61 94.11 94.83 92.42 93.71 94.27 95.05 91.41 93.73 93.76 92.98 90.42 91.19 93.26 91.38 92.52 92.23 91.84
1251 372 32 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 95.11 92.53 95.55 95.16 93.85 94.03 94.41 92.07 94.51 93.42 92.55 91.59 93.51 95.19 94.72 91.92 94.28 94.18 91.56 91.46 92.31 91.71 92.61 92.48 91.59
1260 372 32 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 92.88 94.45 95.52 90.67 93.58 92.50 93.09 93.57 93.46 93.08 94.77 93.14 90.79 95.07 94.83 94.46 94.72 95.26 89.65 93.55 92.25 92.07 92.46 90.73 93.48
1263 372 32 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 92.24 91.34 93.26 92.89 93.62 90.76 93.34 91.42 94.12 94.13 93.20 91.00 92.69 94.40 93.12 89.32 95.07 93.08 92.03 91.87 92.65 93.02 93.84 91.01 91.14
1312 372 32 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 92.67 93.78 93.03 93.57 91.01 92.14 93.04 91.88 93.90 93.20 92.43 92.92 93.42 95.67 91.26 94.35 94.35 92.33 92.64 91.42 92.33 88.10 92.59 92.37 92.70
1315 372 32 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 92.98 94.03 95.40 92.81 95.78 92.23 92.53 95.18 93.85 94.94 92.85 93.72 90.94 94.29 93.74 95.58 95.83 95.02 94.01 92.86 92.91 91.28 92.04 91.79 93.68
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 93.77 92.24 94.35 94.65 91.67 93.58 92.19 95.59 94.99 94.04 91.54 93.31 96.14 94.03 92.89 94.22 94.27 92.88 92.70 91.54 92.77 94.03 92.88 91.70 92.11
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 95.61 93.88 93.79 91.83 95.09 93.14 94.62 95.47 91.84 95.14 93.15 93.30 93.50 92.45 93.60 92.66 95.57 93.91 91.36 92.38 92.89 93.63 93.23 91.80 89.53
1376 372 32 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 92.94 94.31 91.99 95.13 93.67 92.17 92.94 93.11 93.43 96.13 92.16 91.78 95.09 92.74 93.20 90.90 91.23 93.75 89.00 89.91 93.70 92.05 94.92 94.21 92.19
1379 372 32 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 94.06 95.54 93.73 96.69 93.83 92.29 94.08 95.31 94.33 94.16 93.29 80.96 94.01 93.76 93.30 93.92 95.86 93.35 92.46 90.53 94.48 93.38 90.77 92.85 91.92
1388 372 32 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 92.32 93.26 93.43 95.35 93.09 93.35 92.41 91.72 94.86 93.67 93.16 93.16 94.02 94.38 95.41 93.69 94.55 90.73 92.87 92.55 94.68 89.85 92.98 91.12 93.54
1391 372 32 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 93.84 92.61 92.57 95.36 93.24 94.27 92.41 93.53 94.37 95.15 91.97 92.96 93.49 92.24 95.03 94.06 94.99 93.61 93.26 91.46 94.60 93.17 92.45 92.70 93.09
1440 372 32 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 93.17 94.12 92.75 92.46 85.23 92.12 94.78 92.24 95.16 94.49 92.14 91.31 93.46 95.29 93.75 94.14 94.59 88.98 92.87 92.60 92.03 92.96 93.55 91.44 92.60
1443 372 32 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 93.92 93.06 92.99 93.89 94.29 92.26 93.41 94.51 94.81 93.54 93.65 93.22 94.35 93.93 91.75 93.89 95.55 94.22 93.40 92.07 92.81 90.48 91.76 90.04 91.65
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 93.13 95.05 94.69 95.44 94.98 92.47 95.77 95.05 95.43 95.01 91.35 93.86 93.54 94.40 93.19 94.88 95.26 95.35 93.28 91.71 91.90 91.84 92.83 93.20 91.62
1455 372 32 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 95.62 95.98 93.77 95.58 94.82 92.98 95.80 95.09 95.10 94.76 95.11 93.80 94.00 94.41 92.36 92.90 95.10 92.48 94.75 91.18 93.76 93.13 92.19 94.19 93.49
1504 372 32 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 93.85 95.55 95.06 94.11 92.14 93.82 93.79 93.84 95.59 94.67 92.95 95.28 95.60 94.15 95.65 95.13 94.97 96.05 92.61 93.14 93.44 93.37 92.30 94.64 92.54
1507 372 32 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 92.69 95.57 96.19 95.69 94.48 92.96 95.41 93.44 94.35 93.70 94.05 93.79 93.76 94.19 93.91 94.49 96.80 93.53 93.70 92.81 92.91 93.72 93.22 91.07 92.12
1516 372 32 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 94.41 94.18 96.01 94.96 95.48 92.44 94.39 93.13 95.32 93.90 94.08 93.46 93.92 93.53 94.57 93.76 95.37 95.18 93.60 93.49 92.23 92.55 93.41 92.00 94.18
1519 372 32 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 92.28 92.65 94.77 92.46 96.35 92.19 94.43 95.35 91.66 92.89 92.41 93.51 93.00 94.59 92.75 94.67 95.54 93.37 92.60 92.67 93.02 93.49 92.21 89.64 92.79
1568 372 32 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 95.03 71.60 93.21 93.94 89.49 92.93 92.57 94.18 90.59 93.84 92.11 92.35 93.87 86.64 95.24 90.48 93.51 91.49 91.23 94.43 92.59 92.06 93.26 92.63 62.35
1571 372 32 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 93.64 94.94 93.39 94.20 94.78 93.74 94.39 94.34 95.48 92.47 93.03 93.30 95.81 93.72 93.78 92.66 94.61 92.51 91.66 91.10 93.47 92.28 93.48 90.21 91.64
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 85.72 85.81 86.24 87.63 84.94 87.47 84.27 85.81 85.83 87.51 88.27 89.92 87.52 85.80 86.03 86.76 90.59 85.74 89.70 87.99 90.48 88.20 43.72 87.94 89.55
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 85.93 86.79 87.17 86.05 84.99 87.28 85.76 86.04 87.79 88.24 89.22 87.85 87.40 87.91 85.73 89.09 88.92 87.09 87.44 89.69 91.22 88.93 88.92 88.60 89.20
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 86.32 86.76 87.05 87.52 86.74 87.02 86.38 87.31 88.17 86.68 88.64 89.54 87.36 87.10 87.99 88.63 86.43 87.45 89.60 88.46 89.09 89.80 90.05 88.30 88.81
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 86.70 85.32 87.35 86.52 86.28 87.35 87.73 86.71 86.79 87.70 89.10 88.22 86.50 86.82 87.90 88.35 87.90 87.53 90.55 88.27 87.58 89.38 90.06 89.91 89.77
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.27 87.65 87.08 85.49 87.92 86.72 86.20 87.75 88.60 89.02 88.44 88.49 89.48 85.41 87.67 88.37 87.00 87.65 89.04 89.17 88.42 89.17 88.13 90.03 90.25
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 87.21 85.68 88.49 87.98 89.55 86.99 87.26 87.18 87.88 87.80 88.27 86.99 87.97 86.66 87.00 86.67 86.82 87.74 87.50 88.64 89.37 89.69 91.14 89.71 87.49
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.47 87.08 84.36 86.55 86.57 88.08 87.45 86.88 87.08 86.79 89.07 88.21 86.33 85.30 88.03 86.91 86.80 87.80 89.13 89.74 90.60 89.02 89.72 88.91 89.06
108 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 87.26 86.15 86.98 86.80 87.01 87.63 85.50 86.17 89.16 88.01 88.29 88.50 89.30 86.56 86.96 86.63 86.66 88.81 88.92 88.35 88.92 87.39 87.13 89.87 90.30
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.54 84.88 87.87 86.70 88.55 87.58 87.46 86.24 89.87 88.57 88.20 89.83 89.44 87.26 87.25 86.37 87.98 89.71 87.20 87.60 90.87 86.13 88.69 88.61 89.97
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 86.47 85.23 87.09 86.92 86.11 86.22 84.78 86.88 86.61 87.75 89.84 89.06 86.93 85.81 87.06 87.97 85.70 88.13 89.07 90.33 87.81 92.61 89.41 88.31 89.96
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 85.50 86.98 87.25 87.08 87.69 90.44 83.91 86.28 43.72 87.61 89.66 89.77 86.61 87.63 88.08 87.40 85.53 87.68 90.02 88.12 90.87 88.35 88.06 87.03 89.98
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.53 86.15 85.32 86.37 83.24 89.48 90.21 88.14 87.93 88.02 86.47 89.64 90.62 86.92 91.48 87.75 87.88 87.74 88.88 91.25 89.24 88.83 90.97 87.81 89.87
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 85.43 88.18 88.08 86.56 84.62 87.21 86.19 86.31 87.31 88.32 88.56 87.75 87.61 89.22 87.36 89.85 85.79 87.26 89.76 89.20 88.95 87.80 89.53 87.47 88.24
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 85.33 86.79 86.24 86.12 85.69 87.93 86.82 87.54 85.88 90.08 88.42 87.90 88.21 87.53 86.26 87.62 88.40 87.56 87.86 88.68 89.91 89.05 88.02 86.67 91.92
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 86.19 86.57 85.85 88.08 43.72 87.68 86.76 86.56 88.23 87.70 87.34 87.72 86.60 87.38 85.76 86.87 84.97 88.22 85.92 88.71 89.70 88.69 88.98 87.98 89.65
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.99 85.29 87.42 87.70 85.80 90.65 86.24 88.33 86.26 86.88 87.69 88.38 88.70 87.21 88.69 86.83 87.12 88.26 88.04 88.31 89.53 90.34 90.14 89.97 89.32
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.14 87.21 88.77 85.25 88.44 87.57 84.43 86.61 85.73 87.44 87.96 87.76 87.43 87.85 89.03 87.65 86.69 86.97 90.06 91.21 88.72 90.81 88.03 91.39 90.79
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 86.14 87.67 86.50 87.07 87.51 89.98 88.49 87.38 87.17 89.53 88.39 89.59 88.90 88.02 86.27 90.24 85.71 85.20 92.18 90.23 88.57 88.39 89.98 91.55 91.02
556 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 86.12 85.43 85.71 84.21 87.99 87.76 87.30 86.55 85.79 91.00 88.08 91.82 87.31 87.38 87.00 87.10 85.69 85.60 91.76 87.93 87.94 89.74 87.72 88.83 87.69
Size of the All data:  (98, 28)
Size of the Sig data:  (19, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
18 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 92.90 93.86 94.48 59.15 88.49 93.59 94.04 92.28 95.47 93.85 95.55 92.81 91.96 90.15 95.32 93.98 92.67 94.88 93.97 92.24 91.80 94.38 48.12 93.50 92.70
10 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 93.13 95.05 94.69 95.44 94.98 92.47 95.77 95.05 95.43 95.01 91.35 93.86 93.54 94.40 93.19 94.88 95.26 95.35 93.28 91.71 91.90 91.84 92.83 93.20 91.62
7 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 91.48 93.32 93.14 93.99 94.56 91.07 94.98 93.16 90.70 91.72 94.03 93.43 93.25 94.91 91.98 93.62 93.00 92.36 91.77 92.57 92.18 92.17 92.03 93.04 91.90
8 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.50 94.49 95.84 94.58 94.74 91.88 93.05 95.50 94.72 93.83 92.63 93.41 95.14 90.84 92.02 94.80 92.96 94.11 93.33 90.77 93.56 91.70 92.99 85.21 91.60
3 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 94.53 92.20 95.85 92.63 95.20 92.51 95.14 93.77 94.01 93.84 91.32 93.29 95.75 92.11 90.58 95.35 95.40 94.08 94.06 93.13 92.86 93.28 94.04 93.57 93.03
5 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 94.26 93.58 95.26 95.27 94.41 92.67 93.13 94.79 93.76 94.20 92.42 93.58 94.05 93.31 93.45 94.08 93.73 94.78 93.32 92.63 94.76 93.40 59.16 91.82 92.89
14 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 96.24 94.29 93.74 93.75 93.28 91.69 94.19 93.51 93.14 94.43 90.43 92.64 94.54 93.88 94.61 95.29 94.85 95.79 93.01 91.10 91.86 92.90 94.19 92.87 93.96
9 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 91.88 93.29 95.20 94.82 94.77 93.29 94.82 93.60 93.93 93.24 91.95 91.98 93.20 96.01 94.10 92.68 96.69 93.88 90.18 91.94 91.58 90.64 93.72 92.75 91.37
6 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.86 94.73 95.05 93.90 92.90 92.66 93.75 96.18 94.07 94.63 92.13 94.32 95.59 94.08 94.54 94.91 91.38 93.53 91.58 91.88 92.28 91.94 92.57 89.92 92.10
13 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 92.64 92.77 95.73 93.19 92.81 92.45 94.94 93.29 95.47 94.32 93.01 93.74 95.71 92.00 95.34 95.65 92.91 94.35 90.31 87.99 91.55 59.11 92.48 85.88 90.90
16 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 94.09 95.24 94.05 92.62 94.14 92.15 92.12 93.46 48.12 93.82 93.25 90.46 93.82 95.88 93.75 93.98 96.53 94.37 90.92 92.84 57.77 94.20 93.51 92.66 93.37
1 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 93.10 96.04 92.29 92.51 88.44 94.01 94.30 94.26 93.53 95.03 94.08 93.63 91.25 94.55 92.24 95.12 94.07 93.49 92.78 92.48 92.64 93.47 91.67 93.16 93.96
11 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 93.77 92.24 94.35 94.65 91.67 93.58 92.19 95.59 94.99 94.04 91.54 93.31 96.14 94.03 92.89 94.22 94.27 92.88 92.70 91.54 92.77 94.03 92.88 91.70 92.11
12 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 95.61 93.88 93.79 91.83 95.09 93.14 94.62 95.47 91.84 95.14 93.15 93.30 93.50 92.45 93.60 92.66 95.57 93.91 91.36 92.38 92.89 93.63 93.23 91.80 89.53
17 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 94.13 93.08 95.22 93.19 48.12 93.79 94.52 92.88 92.19 92.60 91.04 92.06 89.44 94.77 94.66 93.70 94.76 94.09 91.44 90.47 94.16 91.96 91.75 90.94 89.82
2 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 93.62 95.56 94.62 95.98 93.28 93.15 94.36 94.21 90.55 94.30 92.83 92.95 94.24 94.32 92.92 92.19 93.76 93.30 92.21 91.82 92.93 94.06 93.71 91.27 93.49
4 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 92.27 95.17 93.79 93.82 94.48 91.68 94.70 92.62 95.45 92.59 93.04 94.49 93.15 92.86 91.70 95.94 93.29 93.75 92.62 93.04 93.96 94.52 93.33 91.52 90.15
0 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 92.16 92.18 93.59 93.63 94.31 91.73 95.74 92.59 92.72 94.42 91.45 93.78 95.29 93.21 92.47 93.78 93.16 94.60 92.95 92.26 92.80 93.70 93.84 92.30 91.30
15 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 94.48 93.32 91.89 92.43 92.27 92.55 94.13 93.21 94.53 93.09 93.99 92.52 94.53 94.82 92.99 94.64 93.65 95.26 91.49 92.66 91.99 93.32 94.62 94.43 92.69
Size of the test data:  (19, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.17 7.54 8.64 6.27 6.70 6.23 10.16 6.41 8.86 6.57 3.17 4.68 8.78 6.19 8.28 7.68 7.21 6.22 1.24 -2.34 3.74 -33.50 3.07 -2.43 0.94 3
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.05 7.90 6.77 7.29 4.86 5.68 5.87 7.61 5.88 6.40 4.15 6.59 6.08 6.65 6.45 7.41 6.91 7.04 5.82 3.99 5.39 3.71 -31.98 2.11 5.40 1
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.13 7.96 5.02 8.57 6.04 4.11 10.27 6.01 9.72 5.15 5.08 6.73 5.72 5.01 2.67 8.29 6.60 6.78 2.56 1.83 5.24 3.71 5.30 0.13 -0.64 1
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.28 7.09 7.55 5.71 9.40 5.21 7.80 7.93 5.96 5.06 4.73 5.40 5.29 4.92 7.34 5.04 7.17 6.35 3.50 3.70 2.98 4.58 5.21 5.13 -2.39 1
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.59 8.26 6.80 5.54 6.45 1.71 8.21 7.18 4.40 6.21 3.59 0.69 7.21 8.25 5.67 6.58 11.00 6.69 0.90 4.72 -33.10 5.85 5.45 5.63 3.39 1
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.18 8.05 8.24 -28.48 3.55 6.12 9.77 6.47 9.64 6.34 7.28 2.89 4.44 4.35 9.29 7.22 2.08 9.14 4.27 4.25 1.32 6.18 4.40 5.56 3.15 1
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.80 9.17 8.49 8.06 8.46 4.53 5.32 8.79 7.93 6.13 3.53 5.19 8.64 4.02 4.12 6.45 5.06 6.58 2.78 2.50 5.98 2.32 2.93 -4.70 1.83 1
556 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.36 7.89 6.18 8.22 4.28 4.79 6.83 6.66 8.74 2.09 5.91 0.70 7.22 7.44 5.99 7.54 7.96 9.66 -0.27 4.73 4.05 3.58 6.90 5.60 5.00 1
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.77 7.21 9.38 7.20 6.71 3.61 6.74 6.63 6.06 7.64 1.36 4.43 8.21 8.58 6.58 8.38 8.05 7.99 3.88 1.36 1.26 3.88 4.47 3.96 4.90 0
108 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.62 7.14 8.22 8.02 7.76 5.66 9.32 7.43 4.77 5.23 3.66 3.48 3.90 9.45 7.14 6.05 10.03 5.07 1.26 3.59 2.66 3.25 6.59 2.88 1.07 0
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.32 9.85 7.18 7.20 4.35 5.08 6.29 9.94 4.20 6.06 3.93 4.49 6.15 6.82 7.29 8.54 3.40 3.82 4.38 4.28 1.41 5.81 3.88 1.31 2.13 0
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.20 8.26 7.52 9.39 9.99 5.19 10.01 9.01 7.64 6.77 2.13 6.01 6.14 6.49 7.46 5.79 6.34 8.26 5.84 2.02 0.68 2.91 3.91 4.60 2.42 0
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.26 4.55 8.77 7.14 7.28 5.79 8.94 6.02 5.41 4.82 2.88 4.80 6.27 6.70 2.91 6.98 8.40 6.43 5.02 3.96 4.44 4.11 5.91 3.54 2.78 0
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.57 9.89 6.97 6.14 5.20 4.53 4.09 6.12 5.60 7.01 7.61 3.99 0.63 7.63 0.76 7.37 6.19 5.75 3.90 1.23 3.40 4.64 0.70 5.35 4.09 0
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.34 4.06 6.27 8.09 7.05 6.37 6.00 9.28 7.68 5.72 2.98 5.56 8.53 4.81 5.53 4.37 8.48 5.62 2.94 2.34 3.82 6.23 3.35 4.23 3.87 0
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.94 6.51 9.37 5.11 4.40 6.11 7.76 6.32 3.96 4.90 3.70 4.34 2.84 7.39 8.90 6.83 9.79 5.87 5.52 1.76 4.46 3.27 2.77 2.96 0.17 0
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.63 10.27 7.20 8.28 7.48 2.50 8.12 5.88 4.29 7.42 5.14 4.57 5.54 7.11 4.23 5.36 6.64 5.04 4.17 3.51 3.40 3.72 3.57 1.30 4.17 0
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.16 6.56 6.09 6.47 7.82 4.05 8.60 5.85 2.53 5.04 5.39 3.89 5.89 7.81 3.99 4.99 6.57 4.91 2.17 4.11 3.09 2.37 1.98 4.74 3.09 0
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.02 4.51 7.09 6.56 6.80 1.75 7.25 5.21 5.55 4.89 3.06 4.19 6.39 5.19 6.20 3.54 7.45 9.40 0.77 2.03 4.23 5.31 3.86 0.75 0.28 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_26 89.623158 1.088802
mAP_valid_abs_values_21 89.357368 1.085571
mAP_valid_abs_values_19 89.085789 1.550263
mAP_valid_abs_values_22 89.069474 1.367997
mAP_valid_abs_values_20 89.046316 1.085737
mAP_valid_abs_values_25 88.888947 1.346130
mAP_valid_abs_values_12 88.786316 1.147559
mAP_valid_abs_values_11 88.416316 0.784830
mAP_valid_abs_values_10 88.139474 1.112372
mAP_valid_abs_values_6 87.949474 1.254793
mAP_valid_abs_values_13 87.906316 1.202443
mAP_valid_abs_values_16 87.740000 1.109920
mAP_valid_abs_values_18 87.481053 1.076455
mAP_valid_abs_values_15 87.450000 1.354732
mAP_valid_abs_values_14 87.040526 0.977488
mAP_valid_abs_values_17 86.977895 1.384628
mAP_valid_abs_values_3 86.885263 1.095893
mAP_valid_abs_values_8 86.877368 0.713737
mAP_valid_abs_values_23 86.757895 10.481356
mAP_valid_abs_values_4 86.663158 0.974765
mAP_valid_abs_values_7 86.481053 1.548870
mAP_valid_abs_values_2 86.401053 0.950777
mAP_valid_abs_values 86.276842 0.964135
mAP_valid_abs_values_9 85.042105 10.076121
mAP_valid_abs_values_5 84.387368 9.971664


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_3 94.345789 1.125543
mAP_test_abs_values_16 94.287895 1.039683
mAP_test_abs_values_7 94.236316 1.023796
mAP_test_abs_values_18 94.145263 0.857713
mAP_test_abs_values_17 94.100526 1.378427
mAP_test_abs_values_8 93.969474 1.159399
mAP_test_abs_values_2 93.910000 1.177474
mAP_test_abs_values_10 93.900000 0.908124
mAP_test_abs_values_13 93.899474 1.690419
mAP_test_abs_values_14 93.609474 1.573024
mAP_test_abs_values 93.507895 1.229479
mAP_test_abs_values_15 93.281579 1.288113
mAP_test_abs_values_12 93.134737 0.932258
average_map 92.748105 1.149440
mAP_test_abs_values_6 92.634737 0.814578
mAP_test_abs_values_11 92.588947 1.279613
mAP_test_abs_values_19 92.277895 1.149974
mAP_test_abs_values_26 92.025789 1.318582
mAP_test_abs_values_4 91.967368 8.027002
mAP_test_abs_values_20 91.865789 1.189521
mAP_test_abs_values_25 91.660000 2.404507
mAP_test_abs_values_9 91.295789 10.566407
mAP_test_abs_values_22 91.276316 7.862989
mAP_test_abs_values_5 90.944211 10.557963
mAP_test_abs_values_21 90.854737 8.062013
mAP_test_abs_values_23 88.982632 12.615593
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 85.93 86.79 87.17 86.05 84.99 87.28 85.76 86.04 87.79 88.24 89.22 87.85 87.40 87.91 85.73 89.09 88.92 87.09 87.44 89.69 91.22 88.93 88.92 88.60 89.20
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 86.32 86.76 87.05 87.52 86.74 87.02 86.38 87.31 88.17 86.68 88.64 89.54 87.36 87.10 87.99 88.63 86.43 87.45 89.60 88.46 89.09 89.80 90.05 88.30 88.81
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 86.70 85.32 87.35 86.52 86.28 87.35 87.73 86.71 86.79 87.70 89.10 88.22 86.50 86.82 87.90 88.35 87.90 87.53 90.55 88.27 87.58 89.38 90.06 89.91 89.77
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.27 87.65 87.08 85.49 87.92 86.72 86.20 87.75 88.60 89.02 88.44 88.49 89.48 85.41 87.67 88.37 87.00 87.65 89.04 89.17 88.42 89.17 88.13 90.03 90.25
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 87.21 85.68 88.49 87.98 89.55 86.99 87.26 87.18 87.88 87.80 88.27 86.99 87.97 86.66 87.00 86.67 86.82 87.74 87.50 88.64 89.37 89.69 91.14 89.71 87.49
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.47 87.08 84.36 86.55 86.57 88.08 87.45 86.88 87.08 86.79 89.07 88.21 86.33 85.30 88.03 86.91 86.80 87.80 89.13 89.74 90.60 89.02 89.72 88.91 89.06
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.54 84.88 87.87 86.70 88.55 87.58 87.46 86.24 89.87 88.57 88.20 89.83 89.44 87.26 87.25 86.37 87.98 89.71 87.20 87.60 90.87 86.13 88.69 88.61 89.97
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.53 86.15 85.32 86.37 83.24 89.48 90.21 88.14 87.93 88.02 86.47 89.64 90.62 86.92 91.48 87.75 87.88 87.74 88.88 91.25 89.24 88.83 90.97 87.81 89.87
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 85.43 88.18 88.08 86.56 84.62 87.21 86.19 86.31 87.31 88.32 88.56 87.75 87.61 89.22 87.36 89.85 85.79 87.26 89.76 89.20 88.95 87.80 89.53 87.47 88.24
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.99 85.29 87.42 87.70 85.80 90.65 86.24 88.33 86.26 86.88 87.69 88.38 88.70 87.21 88.69 86.83 87.12 88.26 88.04 88.31 89.53 90.34 90.14 89.97 89.32
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.14 87.21 88.77 85.25 88.44 87.57 84.43 86.61 85.73 87.44 87.96 87.76 87.43 87.85 89.03 87.65 86.69 86.97 90.06 91.21 88.72 90.81 88.03 91.39 90.79
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 86.14 87.67 86.50 87.07 87.51 89.98 88.49 87.38 87.17 89.53 88.39 89.59 88.90 88.02 86.27 90.24 85.71 85.20 92.18 90.23 88.57 88.39 89.98 91.55 91.02
Size of the All data:  (98, 28)
Size of the Sig data:  (12, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
9 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 93.13 95.05 94.69 95.44 94.98 92.47 95.77 95.05 95.43 95.01 91.35 93.86 93.54 94.40 93.19 94.88 95.26 95.35 93.28 91.71 91.90 91.84 92.83 93.20 91.62
7 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 91.48 93.32 93.14 93.99 94.56 91.07 94.98 93.16 90.70 91.72 94.03 93.43 93.25 94.91 91.98 93.62 93.00 92.36 91.77 92.57 92.18 92.17 92.03 93.04 91.90
8 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.50 94.49 95.84 94.58 94.74 91.88 93.05 95.50 94.72 93.83 92.63 93.41 95.14 90.84 92.02 94.80 92.96 94.11 93.33 90.77 93.56 91.70 92.99 85.21 91.60
3 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 94.53 92.20 95.85 92.63 95.20 92.51 95.14 93.77 94.01 93.84 91.32 93.29 95.75 92.11 90.58 95.35 95.40 94.08 94.06 93.13 92.86 93.28 94.04 93.57 93.03
5 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 94.26 93.58 95.26 95.27 94.41 92.67 93.13 94.79 93.76 94.20 92.42 93.58 94.05 93.31 93.45 94.08 93.73 94.78 93.32 92.63 94.76 93.40 59.16 91.82 92.89
11 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 96.24 94.29 93.74 93.75 93.28 91.69 94.19 93.51 93.14 94.43 90.43 92.64 94.54 93.88 94.61 95.29 94.85 95.79 93.01 91.10 91.86 92.90 94.19 92.87 93.96
6 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.86 94.73 95.05 93.90 92.90 92.66 93.75 96.18 94.07 94.63 92.13 94.32 95.59 94.08 94.54 94.91 91.38 93.53 91.58 91.88 92.28 91.94 92.57 89.92 92.10
1 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 93.10 96.04 92.29 92.51 88.44 94.01 94.30 94.26 93.53 95.03 94.08 93.63 91.25 94.55 92.24 95.12 94.07 93.49 92.78 92.48 92.64 93.47 91.67 93.16 93.96
10 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 93.77 92.24 94.35 94.65 91.67 93.58 92.19 95.59 94.99 94.04 91.54 93.31 96.14 94.03 92.89 94.22 94.27 92.88 92.70 91.54 92.77 94.03 92.88 91.70 92.11
2 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 93.62 95.56 94.62 95.98 93.28 93.15 94.36 94.21 90.55 94.30 92.83 92.95 94.24 94.32 92.92 92.19 93.76 93.30 92.21 91.82 92.93 94.06 93.71 91.27 93.49
4 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 92.27 95.17 93.79 93.82 94.48 91.68 94.70 92.62 95.45 92.59 93.04 94.49 93.15 92.86 91.70 95.94 93.29 93.75 92.62 93.04 93.96 94.52 93.33 91.52 90.15
0 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 92.16 92.18 93.59 93.63 94.31 91.73 95.74 92.59 92.72 94.42 91.45 93.78 95.29 93.21 92.47 93.78 93.16 94.60 92.95 92.26 92.80 93.70 93.84 92.30 91.30
Size of the test data:  (12, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

key_values = ['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']
print('Are the keys of the valid and test dfs same?: ',dt_mw[key_values].equals(test_data_mw1[key_values]))
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.80 9.17 8.49 8.06 8.46 4.53 5.32 8.79 7.93 6.13 3.53 5.19 8.64 4.02 4.12 6.45 5.06 6.58 2.78 2.50 5.98 2.32 2.93 -4.70 1.83 1
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.05 7.90 6.77 7.29 4.86 5.68 5.87 7.61 5.88 6.40 4.15 6.59 6.08 6.65 6.45 7.41 6.91 7.04 5.82 3.99 5.39 3.71 -31.98 2.11 5.40 1
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.13 7.96 5.02 8.57 6.04 4.11 10.27 6.01 9.72 5.15 5.08 6.73 5.72 5.01 2.67 8.29 6.60 6.78 2.56 1.83 5.24 3.71 5.30 0.13 -0.64 1
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.20 8.26 7.52 9.39 9.99 5.19 10.01 9.01 7.64 6.77 2.13 6.01 6.14 6.49 7.46 5.79 6.34 8.26 5.84 2.02 0.68 2.91 3.91 4.60 2.42 0
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.16 6.56 6.09 6.47 7.82 4.05 8.60 5.85 2.53 5.04 5.39 3.89 5.89 7.81 3.99 4.99 6.57 4.91 2.17 4.11 3.09 2.37 1.98 4.74 3.09 0
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.26 4.55 8.77 7.14 7.28 5.79 8.94 6.02 5.41 4.82 2.88 4.80 6.27 6.70 2.91 6.98 8.40 6.43 5.02 3.96 4.44 4.11 5.91 3.54 2.78 0
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.77 7.21 9.38 7.20 6.71 3.61 6.74 6.63 6.06 7.64 1.36 4.43 8.21 8.58 6.58 8.38 8.05 7.99 3.88 1.36 1.26 3.88 4.47 3.96 4.90 0
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.32 9.85 7.18 7.20 4.35 5.08 6.29 9.94 4.20 6.06 3.93 4.49 6.15 6.82 7.29 8.54 3.40 3.82 4.38 4.28 1.41 5.81 3.88 1.31 2.13 0
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.57 9.89 6.97 6.14 5.20 4.53 4.09 6.12 5.60 7.01 7.61 3.99 0.63 7.63 0.76 7.37 6.19 5.75 3.90 1.23 3.40 4.64 0.70 5.35 4.09 0
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.34 4.06 6.27 8.09 7.05 6.37 6.00 9.28 7.68 5.72 2.98 5.56 8.53 4.81 5.53 4.37 8.48 5.62 2.94 2.34 3.82 6.23 3.35 4.23 3.87 0
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.63 10.27 7.20 8.28 7.48 2.50 8.12 5.88 4.29 7.42 5.14 4.57 5.54 7.11 4.23 5.36 6.64 5.04 4.17 3.51 3.40 3.72 3.57 1.30 4.17 0
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.02 4.51 7.09 6.56 6.80 1.75 7.25 5.21 5.55 4.89 3.06 4.19 6.39 5.19 6.20 3.54 7.45 9.40 0.77 2.03 4.23 5.31 3.86 0.75 0.28 0
Are the keys of the valid and test dfs same?:  False

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_23 89.613333 1.001457
mAP_valid_abs_values_26 89.482500 1.017297
mAP_valid_abs_values_25 89.355000 1.300472
mAP_valid_abs_values_21 89.346667 1.072180
mAP_valid_abs_values_20 89.314167 1.158286
mAP_valid_abs_values_19 89.115000 1.455257
mAP_valid_abs_values_22 89.024167 1.222415
mAP_valid_abs_values_12 88.520833 0.920607
mAP_valid_abs_values_11 88.334167 0.746123
mAP_valid_abs_values_13 88.145000 1.295534
mAP_valid_abs_values_16 88.059167 1.258075
mAP_valid_abs_values_6 87.992500 1.303290
mAP_valid_abs_values_10 87.915833 0.888620
mAP_valid_abs_values_15 87.866667 1.466966
mAP_valid_abs_values_9 87.548333 1.093666
mAP_valid_abs_values_18 87.533333 1.021410
mAP_valid_abs_values_14 87.140000 1.086211
mAP_valid_abs_values_3 87.121667 1.260497
mAP_valid_abs_values_17 87.086667 0.942775
mAP_valid_abs_values_8 87.073333 0.742555
mAP_valid_abs_values_7 86.983333 1.475129
mAP_valid_abs_values_5 86.684167 1.832561
mAP_valid_abs_values_4 86.646667 0.830447
mAP_valid_abs_values_2 86.555000 1.076421
mAP_valid_abs_values 86.389167 1.117403


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_3 94.380208 1.060424
mAP_test_abs_values_17 94.047917 1.308239
mAP_test_abs_values_13 94.010000 1.274458
mAP_test_abs_values_10 93.969375 0.840849
mAP_test_abs_values_4 93.921875 1.318254
mAP_test_abs_values_8 93.868750 1.137492
mAP_test_abs_values_14 93.770833 1.370117
mAP_test_abs_values 93.608958 1.126441
mAP_test_abs_values_18 93.466042 1.417141
mAP_test_abs_values_5 93.438333 1.878001
mAP_test_abs_values_12 93.129167 0.857018
mAP_test_abs_values_9 93.090833 6.731690
mAP_test_abs_values_15 92.981250 1.145863
average_map 92.800125 1.150285
mAP_test_abs_values_19 92.611667 1.244397
mAP_test_abs_values_11 92.546875 1.062498
mAP_test_abs_values_7 92.255833 9.350205
mAP_test_abs_values_6 92.234375 0.811699
mAP_test_abs_values_16 92.146875 9.339141
mAP_test_abs_values_20 92.142083 1.087787
mAP_test_abs_values_22 92.139583 5.044086
mAP_test_abs_values_26 91.914375 1.499664
mAP_test_abs_values_2 91.724375 8.675925
mAP_test_abs_values_25 91.643125 2.238106
mAP_test_abs_values_23 91.098958 8.427058
mAP_test_abs_values_21 89.861458 9.058537


Summary using radar plot

Code
def extract_number(text):
    if isinstance(text, str):
        matches = re.findall(r'\d+', text)
        return int(matches[0]) if matches else 1
    return 1

res_valid1['id'] = res_valid1.index.to_series().apply(extract_number)
res_test1['id'] = res_test1.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid1,res_test1])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test1 = res_test1.sort_values(by=['id']).reset_index().query("index !='average_map'")
data_range1 = np.array(list(res_test1['mean']) + list(res_valid1['mean']))
categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test1['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid1['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()

##############


res_valid2['id'] = res_valid2.index.to_series().apply(extract_number)
res_test2['id'] = res_test2.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid2,res_test2])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test2 = res_test2.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res_test2['mean']) + list(res_valid2['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test2['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid2['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()




  • In these experimental results, the thresholding is based on a fixed value of 0. This decision is informed by the fact that the binary-like hash values are symmetrically distributed between -1 and 1.
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
32 372 32 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 84.31 84.04 85.93 87.19 86.39 84.06 84.62 84.74 86.46 85.18 88.63 86.20 86.94 84.54 84.80 85.63 88.12 87.64 87.13 87.82 84.72 87.71 89.13 87.89 86.72
35 372 32 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 84.35 85.16 86.51 84.89 85.95 85.98 86.27 85.65 85.08 85.31 89.38 87.45 85.32 83.38 86.84 87.45 85.82 43.72 88.81 84.95 89.39 85.94 86.46 89.80 88.16
44 372 32 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 85.96 85.59 85.49 85.19 83.88 85.89 86.52 88.78 85.56 85.36 87.82 87.53 85.74 85.68 87.69 86.41 86.65 87.16 88.21 87.96 90.19 89.02 89.74 87.93 89.19
47 372 32 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 85.87 86.44 85.19 86.03 84.77 90.44 82.24 86.48 85.18 85.96 87.39 85.60 85.18 85.62 87.64 86.41 86.86 87.66 88.48 86.82 88.17 87.88 85.48 87.90 86.77
96 372 32 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 84.30 86.50 85.12 83.83 84.80 87.50 43.72 88.58 86.78 87.46 89.44 89.08 86.27 88.21 88.22 43.72 86.57 86.72 89.45 88.68 89.03 89.22 88.34 87.33 86.57
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.42 86.66 84.35 86.37 85.86 88.07 87.45 86.78 86.34 86.78 87.78 88.20 86.33 85.27 87.98 86.91 86.51 87.20 89.13 89.74 90.59 88.83 89.70 88.85 88.70
108 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 87.14 86.12 86.93 86.42 86.69 87.45 85.50 85.75 89.14 86.49 88.28 88.49 88.09 86.37 86.88 86.41 86.63 88.65 88.82 87.98 88.90 87.16 87.13 89.85 89.99
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.30 84.87 87.86 86.25 88.54 87.57 87.32 85.68 89.37 88.30 88.20 89.58 89.44 86.68 87.06 86.35 86.01 88.71 87.18 87.60 90.85 85.89 88.69 88.60 89.95
160 372 32 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 86.51 86.54 84.32 84.84 84.95 86.69 84.18 86.53 86.00 85.33 86.99 86.48 86.18 87.75 85.43 79.53 86.74 83.66 88.30 90.34 87.17 87.96 85.78 88.02 88.85
163 372 32 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 85.36 86.78 85.53 85.62 78.22 86.47 85.32 86.26 88.23 87.51 87.70 88.55 87.08 87.57 87.64 84.70 86.11 85.68 89.07 87.63 90.72 86.94 86.64 88.52 90.09
172 372 32 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.38 85.26 85.22 86.82 87.16 88.07 86.87 43.72 87.42 87.28 86.24 85.46 86.88 43.72 84.60 88.26 86.92 86.24 89.14 87.61 86.63 87.44 43.72 88.81 86.80
175 372 32 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 83.16 88.60 85.04 85.52 86.39 86.92 84.30 88.31 88.16 85.55 88.13 89.59 89.48 87.57 85.25 88.03 86.30 85.66 88.69 88.61 89.02 88.05 88.19 87.98 87.99
224 372 32 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 82.63 84.16 86.58 85.32 82.73 87.94 83.67 86.38 85.54 87.01 88.05 88.94 85.13 86.99 86.58 87.13 87.18 85.80 87.87 88.36 88.42 87.72 88.35 86.93 87.54
227 372 32 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 86.98 85.44 86.56 87.65 84.46 87.95 86.15 86.01 84.96 85.15 86.97 86.78 85.99 85.83 89.61 86.42 85.60 86.68 89.03 87.74 86.16 86.16 86.90 87.71 87.46
236 372 32 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 87.45 85.17 85.84 83.80 86.43 85.65 84.65 86.26 87.07 83.87 88.27 85.98 85.85 88.32 85.86 84.88 84.81 86.37 88.41 88.38 90.44 89.61 88.18 89.90 87.83
239 372 32 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 85.42 85.42 85.54 85.23 87.12 86.68 83.04 84.49 83.50 86.21 87.63 91.61 85.86 86.00 86.32 87.59 86.93 86.45 88.45 87.61 89.61 87.18 88.67 88.58 88.06
288 372 32 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.03 83.88 84.60 86.51 85.45 85.51 86.20 88.17 88.73 85.81 86.22 88.38 83.77 87.31 85.14 86.11 43.72 84.85 43.72 86.53 88.60 86.69 88.65 88.44 88.58
291 372 32 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 84.52 86.89 86.53 83.71 85.18 85.43 84.76 85.28 87.50 85.92 88.09 87.30 88.80 85.49 87.25 87.97 86.67 85.56 86.50 87.52 88.74 88.43 88.16 89.34 87.53
300 372 32 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 86.67 86.60 86.23 83.28 86.42 86.37 86.54 89.26 85.25 85.59 87.28 87.30 87.86 84.83 86.27 87.73 87.31 85.83 89.32 88.78 88.10 88.29 43.72 87.05 87.93
303 372 32 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 85.05 86.07 86.60 83.70 86.98 88.62 86.08 87.38 86.42 87.48 88.10 87.68 87.27 87.08 86.97 86.42 88.79 87.14 88.09 87.75 88.16 86.22 89.38 89.43 87.77
352 372 32 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 85.75 83.50 85.70 84.00 85.98 86.72 81.62 87.33 84.24 87.65 87.25 88.11 87.50 88.50 87.18 87.58 85.98 87.41 86.69 88.82 89.76 87.52 87.09 87.57 86.67
355 372 32 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 84.90 84.63 84.62 84.80 86.51 86.73 87.04 86.10 87.08 87.07 86.10 87.27 86.46 85.69 85.42 87.32 86.48 88.19 87.28 88.50 88.24 87.36 89.09 87.09 88.38
364 372 32 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 85.79 88.77 86.03 84.09 86.58 86.27 86.72 88.48 86.35 88.62 87.47 87.08 85.71 84.43 89.09 86.81 88.67 87.24 88.92 88.40 89.00 89.86 88.20 81.36 88.05
367 372 32 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 86.33 86.86 85.54 89.15 86.08 86.74 85.40 87.35 88.36 86.29 88.20 86.72 88.51 85.72 86.91 87.22 86.80 86.62 89.00 87.47 89.87 88.35 86.95 88.72 87.41
416 372 32 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 85.48 84.98 84.76 82.01 85.13 85.95 85.12 86.39 85.52 88.34 84.46 85.70 87.90 87.41 85.01 87.78 87.36 87.55 87.79 89.87 86.88 88.46 83.26 86.52 89.29
419 372 32 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.29 84.90 85.67 85.85 84.71 85.33 85.43 86.65 86.64 86.38 87.41 86.15 87.20 86.34 89.07 87.52 85.25 87.17 88.29 87.00 88.35 88.87 90.13 87.53 89.84
428 372 32 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 86.23 89.22 85.11 85.17 86.29 88.74 85.41 85.19 84.92 88.14 87.76 86.73 87.89 86.42 86.99 87.29 87.26 85.14 89.12 88.20 89.69 89.38 88.87 89.75 86.76
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 85.72 85.64 86.08 86.95 84.17 87.46 84.13 85.69 85.26 87.48 88.10 89.88 87.50 85.01 85.96 86.58 90.29 85.16 89.55 87.85 90.40 88.13 43.72 87.04 88.91
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 86.17 84.98 86.86 86.45 86.11 86.21 84.72 86.26 86.57 87.74 89.45 88.88 86.63 85.74 86.97 87.84 85.60 88.13 89.07 89.96 87.34 92.58 88.91 88.19 89.47
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 85.38 86.74 87.22 87.06 87.69 89.67 83.53 86.28 43.72 87.40 89.52 89.77 86.61 87.14 87.93 87.40 85.41 87.50 90.02 87.86 90.82 88.34 87.78 86.14 89.74
492 372 32 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 84.67 86.84 85.39 86.52 84.09 84.87 84.68 84.53 86.24 85.67 87.12 90.33 86.83 87.08 86.92 87.46 88.69 88.75 88.08 88.08 89.78 88.09 89.51 88.95 88.92
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.36 85.76 85.16 86.10 83.23 88.14 89.99 87.93 87.86 88.02 86.47 89.21 90.60 86.89 89.18 87.73 87.43 87.74 88.73 91.18 89.22 88.78 90.97 87.81 89.84
544 372 32 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 85.71 84.84 84.79 85.10 85.47 87.00 83.61 85.53 86.67 85.60 86.32 86.58 88.25 84.91 85.71 88.05 82.84 88.30 92.18 87.97 89.53 90.33 86.33 88.23 88.53
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 86.14 87.66 86.50 87.01 87.47 89.74 87.98 87.14 87.17 89.51 88.39 89.23 88.88 87.79 86.27 90.24 85.51 84.89 92.18 89.88 88.57 88.38 89.94 91.49 90.34
556 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 85.78 85.43 85.27 84.18 87.69 86.67 87.23 86.48 85.79 91.00 88.08 91.82 87.31 87.12 86.77 87.10 85.69 85.24 91.76 87.93 87.94 89.72 87.41 88.59 87.66
559 372 32 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 85.56 84.04 87.13 86.30 84.11 87.30 84.34 87.79 84.94 83.43 89.31 87.27 87.17 85.45 89.60 87.13 85.04 86.15 89.72 90.16 88.81 89.15 88.30 89.00 88.98
608 372 32 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 83.47 83.33 83.83 84.09 81.92 84.58 43.72 85.99 84.26 86.35 86.24 86.92 87.10 86.20 86.97 85.16 87.05 84.55 86.10 87.27 87.01 88.29 87.91 87.96 87.93
611 372 32 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 86.29 82.47 87.03 85.67 85.82 87.28 84.15 86.58 85.96 84.21 88.46 88.77 88.27 86.69 85.78 86.15 84.13 86.70 87.59 86.96 88.50 87.46 88.40 86.39 85.55
620 372 32 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.02 85.36 88.91 85.07 85.83 86.21 84.79 89.05 86.42 84.01 87.94 87.18 86.08 88.29 87.53 87.87 89.40 84.82 86.30 87.36 88.35 88.56 87.77 87.34 88.30
623 372 32 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 86.89 89.90 87.67 85.29 84.82 89.14 84.84 86.13 84.68 84.64 87.65 87.63 87.84 85.62 87.63 85.27 87.53 86.15 87.35 88.39 87.64 87.31 89.85 88.26 89.54
672 372 32 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 83.87 86.38 84.74 83.80 83.35 86.31 84.60 87.18 86.02 86.93 87.59 86.73 85.22 84.17 85.50 84.68 86.42 87.61 87.56 87.58 86.33 88.39 87.48 87.66 88.39
675 372 32 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.86 88.10 86.01 84.19 85.93 85.72 87.07 86.90 85.08 87.24 87.44 87.21 87.15 84.13 89.21 85.99 87.07 86.01 88.50 88.65 90.26 88.30 88.32 88.64 88.10
684 372 32 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.90 89.16 86.60 84.37 88.12 87.13 85.50 87.29 88.10 86.69 87.24 86.87 85.58 87.42 86.58 87.46 85.88 85.49 86.36 85.05 89.42 88.86 89.37 87.00 89.29
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 86.16 86.66 87.05 86.72 86.68 86.93 86.20 86.77 88.17 86.60 88.53 89.26 86.85 86.31 87.84 87.96 86.16 87.39 89.55 88.46 87.63 89.79 90.02 88.27 88.81
736 372 32 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 85.20 53.60 86.12 87.29 82.02 88.01 83.69 86.58 87.42 88.36 86.51 87.81 87.78 88.55 85.02 87.82 83.50 86.91 86.41 89.09 88.29 89.72 89.80 87.55 87.84
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 86.08 86.03 85.85 88.05 43.72 87.04 86.76 86.55 87.97 87.70 87.19 87.72 86.59 87.14 85.52 86.54 84.93 88.22 85.70 88.45 89.70 88.59 88.98 86.52 89.49
748 372 32 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 86.26 86.21 83.40 86.87 85.25 86.34 85.05 84.93 84.35 86.49 86.72 88.49 85.09 85.93 87.53 88.11 85.29 85.91 88.24 89.85 87.23 89.11 88.56 89.69 87.04
751 372 32 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 85.92 87.19 84.87 86.93 85.30 85.99 87.39 86.97 87.29 85.09 88.60 87.79 87.40 88.61 87.39 86.89 88.18 85.63 86.98 89.86 89.17 88.81 88.68 89.74 87.53
800 372 32 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 86.97 86.37 85.12 89.55 88.55 85.02 84.69 84.77 84.39 86.52 85.15 88.73 87.53 87.27 86.85 86.76 85.36 86.73 90.44 87.61 88.12 88.19 88.80 86.75 86.19
803 372 32 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 84.66 86.28 85.76 85.55 86.61 87.54 85.29 85.27 85.34 85.38 87.24 87.45 87.45 83.55 86.92 86.48 86.69 88.49 87.98 88.95 89.01 86.54 88.06 87.63 88.07
812 372 32 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 85.34 85.51 85.36 89.40 85.70 86.87 83.17 87.52 86.99 86.44 86.52 88.46 84.92 86.99 84.34 86.40 86.22 86.50 87.96 88.75 88.03 86.09 88.44 89.21 86.52
815 372 32 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 83.33 86.70 85.90 87.40 83.70 84.84 84.49 85.11 86.02 86.38 87.57 88.58 87.36 87.18 86.19 87.59 83.24 86.95 87.96 88.00 88.35 86.96 87.93 87.05 88.21
864 372 32 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 84.65 86.51 85.95 85.17 86.22 86.78 85.09 86.27 43.72 87.02 87.74 89.55 86.32 86.61 86.48 84.78 86.36 85.92 88.28 88.41 88.60 88.68 85.46 88.39 89.26
867 372 32 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 86.61 87.05 86.85 87.45 86.28 85.70 85.79 85.84 87.41 84.99 90.08 88.88 85.84 87.81 87.34 86.06 87.96 87.43 89.33 86.30 89.09 88.83 90.59 87.90 87.00
876 372 32 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 87.84 90.38 86.13 85.61 85.27 87.08 85.01 86.81 87.33 84.99 87.00 86.59 85.98 87.18 87.72 89.51 85.72 86.24 86.73 89.31 90.28 86.94 89.05 88.65 87.14
879 372 32 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 87.75 86.15 86.67 87.01 86.22 87.23 86.09 86.79 85.99 85.51 86.44 87.69 85.73 85.90 85.94 85.75 87.12 88.82 88.67 89.02 87.99 88.34 88.07 88.62 87.38
928 372 32 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 84.82 89.97 87.20 85.05 86.09 86.81 82.78 85.86 87.31 88.62 87.30 87.88 85.61 89.76 87.51 85.93 86.13 85.94 86.73 87.35 88.64 87.00 88.84 88.56 83.35
931 372 32 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 84.46 86.52 85.21 84.03 86.37 87.93 85.15 84.52 86.89 86.40 88.62 88.15 84.38 85.85 90.04 87.96 86.23 87.68 86.36 88.56 88.72 89.93 89.38 64.92 89.00
940 372 32 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 83.25 86.75 87.36 86.79 85.60 87.40 85.76 86.08 84.24 84.46 88.56 87.08 88.40 87.75 86.34 87.05 85.03 85.97 87.80 87.85 87.37 88.07 87.77 89.11 88.88
943 372 32 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 86.02 87.71 84.12 87.17 86.24 86.92 85.57 87.44 87.62 85.62 87.03 86.29 86.87 86.42 87.02 85.91 86.43 88.13 88.16 88.61 88.22 88.50 89.42 81.55 86.97
992 372 32 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 83.68 86.19 85.59 83.24 84.78 84.33 85.36 85.27 89.53 86.03 88.86 88.30 87.64 87.63 83.13 87.54 88.42 86.44 88.92 88.90 89.81 89.01 88.63 88.90 82.12
995 372 32 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 86.20 84.40 85.58 84.93 88.62 84.51 86.03 86.43 86.45 84.77 87.25 90.02 86.19 88.22 87.84 86.45 87.74 85.73 86.73 88.37 88.21 85.48 87.95 88.57 87.68
1004 372 32 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 83.89 85.26 89.23 85.75 86.08 86.40 84.98 85.72 85.68 87.74 88.44 83.82 84.20 86.97 86.88 89.54 86.63 86.70 87.15 87.72 88.56 88.66 87.58 87.80 89.16
1007 372 32 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 84.88 85.02 85.52 84.62 89.89 87.49 84.08 88.50 85.73 84.25 85.58 87.96 88.06 87.47 87.85 87.25 88.76 85.00 84.79 87.61 89.84 89.64 88.44 89.44 89.43
1056 372 32 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 86.16 91.52 85.59 84.31 83.82 86.47 85.24 87.60 87.15 84.54 88.29 87.74 86.37 87.66 86.58 87.66 85.14 86.43 88.98 86.84 90.96 89.38 88.02 90.12 89.62
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 86.63 85.26 87.13 84.91 86.23 87.25 87.50 86.35 86.16 87.70 88.94 88.08 86.48 86.69 86.20 88.35 87.90 87.53 90.55 88.22 87.47 89.38 89.85 89.09 89.53
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.26 87.64 86.94 85.23 87.37 86.72 86.13 87.41 88.48 87.73 88.42 88.20 89.48 85.12 87.28 88.36 86.92 87.45 89.00 89.17 88.41 89.15 88.13 89.70 90.25
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 85.91 85.36 88.31 87.63 89.53 86.65 87.26 86.69 87.87 87.72 87.56 86.75 87.83 86.44 86.72 86.26 86.41 87.73 87.01 88.64 89.37 88.74 90.47 89.69 87.35
1120 372 32 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 86.19 86.18 85.06 83.83 87.93 88.76 87.57 88.44 86.88 87.75 89.06 87.24 87.85 85.46 87.93 85.92 87.74 84.71 87.77 90.74 87.55 89.88 88.11 89.27 87.23
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.22 85.28 87.40 86.97 85.51 90.35 86.11 88.33 86.26 86.83 87.45 88.38 88.58 87.14 88.45 86.83 86.75 88.04 88.04 88.06 89.53 90.14 90.03 89.96 89.31
1132 372 32 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 82.33 86.92 85.73 84.39 84.07 87.40 84.74 86.55 87.42 86.68 86.94 90.14 85.79 85.00 88.59 88.54 85.37 85.87 87.63 92.32 89.65 89.59 88.90 87.15 86.09
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.14 86.91 88.76 84.75 88.43 87.26 84.35 86.14 85.73 87.43 87.71 87.63 87.28 87.85 88.83 87.53 86.64 86.60 89.99 91.21 88.72 90.77 87.78 91.36 90.53
1184 372 32 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 83.78 86.92 84.71 88.14 83.79 85.93 84.15 86.32 82.74 85.65 85.79 86.25 84.60 88.97 88.61 87.03 85.24 84.43 87.33 86.20 89.14 87.84 87.67 86.04 87.69
1187 372 32 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 85.49 88.50 85.77 87.67 84.47 86.94 84.97 86.22 87.33 85.74 86.11 88.82 89.09 86.66 88.02 87.47 85.48 86.47 86.78 88.27 86.71 86.91 87.09 89.11 88.54
1196 372 32 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 84.51 83.13 83.22 83.00 86.70 85.83 83.70 85.33 84.92 85.90 87.90 87.68 89.53 86.23 88.67 86.09 87.10 87.11 88.69 90.33 87.14 88.83 87.98 88.91 89.26
1199 372 32 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 84.68 85.09 85.98 83.78 85.38 86.04 86.16 86.68 87.01 85.90 88.34 88.39 85.99 86.15 85.77 87.09 88.95 87.93 84.52 87.29 89.01 87.74 87.56 89.80 88.30
1248 372 32 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 84.47 84.99 85.53 83.56 86.32 87.51 86.40 86.31 85.92 84.93 88.01 87.87 88.54 86.17 86.20 86.88 84.21 85.56 90.51 88.02 90.00 87.98 87.57 86.97 88.08
1251 372 32 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 85.95 86.31 86.34 86.27 86.44 87.69 86.29 85.23 86.27 86.17 88.82 88.72 84.89 86.09 87.65 85.75 85.99 87.97 88.98 88.73 91.12 87.57 87.65 89.23 88.57
1260 372 32 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 86.85 86.02 87.37 86.00 85.23 86.41 85.80 85.82 86.05 87.21 88.02 89.09 86.12 83.73 89.07 86.10 85.64 87.80 88.80 87.80 88.09 87.98 88.43 88.17 87.62
1263 372 32 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 85.60 87.75 86.79 86.91 86.29 86.94 86.65 86.77 87.18 86.86 88.90 88.84 87.97 85.30 85.15 86.74 87.58 86.82 87.66 88.09 88.67 90.38 87.03 89.88 88.07
1312 372 32 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 83.56 84.43 85.96 85.39 87.16 85.32 87.49 88.68 84.70 85.93 86.29 87.64 86.63 86.64 87.60 87.85 87.56 85.64 89.18 90.21 88.59 73.19 85.33 89.23 89.14
1315 372 32 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 84.94 85.99 86.59 84.59 86.37 88.25 86.67 86.55 86.34 87.35 86.90 87.82 85.54 86.79 85.67 86.64 87.13 87.15 86.58 89.25 89.78 87.86 88.99 89.18 87.56
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.79 88.02 88.08 86.31 84.39 86.73 85.75 86.29 87.30 87.91 88.32 87.74 87.61 88.24 87.36 89.60 85.69 87.07 89.42 89.20 88.88 87.71 89.25 87.47 88.23
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 85.33 86.59 86.04 86.11 85.20 87.93 86.65 87.54 85.82 90.05 88.39 87.46 88.11 87.05 85.99 87.61 88.35 86.87 87.54 88.55 89.82 89.05 88.02 86.67 91.92
1376 372 32 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 85.67 85.51 87.99 84.25 85.08 87.55 84.22 87.03 86.95 86.87 87.05 88.02 86.44 84.60 86.56 86.31 87.32 85.36 85.45 86.70 87.70 86.12 87.75 88.94 86.67
1379 372 32 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 83.68 85.16 87.50 83.94 85.56 85.18 84.74 86.03 83.48 85.26 87.62 90.89 85.94 88.14 84.40 88.05 84.87 87.40 87.80 88.24 86.82 85.71 85.05 87.92 88.14
1388 372 32 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 86.12 85.48 86.63 85.41 87.29 85.74 84.37 86.15 85.71 87.05 88.18 87.37 85.56 87.30 88.23 88.60 87.67 85.25 89.34 87.61 88.59 89.48 86.44 87.13 88.01
1391 372 32 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 85.31 88.10 84.84 85.52 84.37 85.39 84.14 87.23 83.62 86.86 87.38 87.01 88.14 86.16 87.13 87.66 85.64 84.52 89.90 88.10 86.80 89.24 88.85 86.33 87.35
1440 372 32 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 85.65 88.95 84.75 87.08 87.62 85.67 85.51 86.65 89.14 85.32 86.98 86.87 86.62 86.51 86.12 87.86 87.75 86.29 86.91 86.82 88.76 89.07 88.87 88.49 87.41
1443 372 32 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 87.51 85.18 87.25 86.33 84.80 84.80 86.19 85.42 87.29 85.36 86.92 86.65 87.12 85.38 87.38 86.48 87.04 86.72 88.67 86.79 87.23 86.98 88.22 88.21 88.43
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 85.91 86.72 87.17 85.85 84.96 87.28 85.76 85.79 87.55 88.23 87.91 87.82 87.36 87.40 85.63 88.80 88.76 86.90 87.44 89.66 91.21 88.90 88.91 87.60 88.98
1455 372 32 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.10 85.05 83.85 86.64 86.52 86.77 84.81 85.53 86.04 85.27 87.08 86.17 84.33 86.16 88.10 85.53 86.00 87.43 87.57 87.25 89.09 88.39 88.83 89.45 87.26
1504 372 32 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 84.84 84.18 90.50 85.84 83.81 87.00 86.81 89.34 86.42 84.02 87.26 88.58 85.80 86.16 85.83 84.44 87.78 86.15 87.88 86.65 86.93 88.91 89.05 82.31 87.56
1507 372 32 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 86.14 85.81 85.80 87.72 86.42 87.76 86.92 86.27 86.83 86.05 86.24 87.43 85.89 84.95 84.77 88.22 86.21 85.13 88.33 86.78 87.22 87.64 88.47 88.21 88.01
1516 372 32 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 83.33 86.61 86.41 85.44 84.88 88.21 85.05 89.00 85.72 84.88 86.28 87.08 87.68 84.68 84.68 87.30 86.22 85.80 87.77 88.61 88.73 88.95 86.24 88.71 88.61
1519 372 32 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 84.64 86.92 85.64 85.74 84.22 85.93 84.97 84.51 84.49 86.25 85.63 88.67 86.93 85.81 85.69 85.89 88.89 85.56 86.56 86.81 87.10 87.86 87.02 88.15 85.87
1568 372 32 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 85.20 85.54 86.16 83.67 84.06 84.38 84.75 86.49 86.59 86.63 86.71 88.15 87.35 85.19 85.03 87.66 83.02 86.77 87.89 89.52 89.24 88.90 87.85 87.89 88.50
1571 372 32 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 83.81 84.43 84.24 83.41 85.02 86.67 84.38 87.81 85.24 83.81 88.73 85.08 86.25 85.41 89.60 85.23 85.50 83.69 88.64 86.82 87.64 89.47 87.09 87.54 88.03


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
32 372 32 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 92.61 92.46 92.68 94.10 91.25 90.33 90.41 94.73 92.78 90.30 91.63 91.89 94.07 94.26 91.20 93.94 91.31 94.30 89.63 90.70 91.31 92.61 90.97 92.26 92.21
35 372 32 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 91.71 93.62 93.40 93.21 91.67 92.42 93.39 93.33 94.75 91.95 91.09 91.07 91.88 93.27 94.18 94.42 94.87 48.12 90.92 91.80 91.99 93.83 90.25 90.66 92.82
44 372 32 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 95.13 92.15 94.41 93.79 94.42 93.82 93.92 94.36 90.80 93.44 91.47 92.88 92.38 94.12 92.49 94.18 91.95 93.96 91.34 93.69 92.13 93.64 92.59 91.61 91.95
47 372 32 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 93.75 94.65 94.17 91.66 93.91 78.74 93.57 93.25 93.59 92.58 92.13 91.73 93.34 93.18 92.44 94.31 93.66 91.17 92.38 91.85 92.44 94.99 93.33 93.88 93.20
96 372 32 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 92.01 94.45 95.81 94.50 92.46 90.85 48.12 92.95 95.06 92.90 91.82 92.63 93.17 94.55 93.62 48.12 94.77 94.10 89.93 91.18 90.58 94.28 91.49 91.71 91.86
99 372 32 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 96.24 94.28 93.74 93.54 94.67 91.69 94.19 93.51 94.20 94.43 93.30 92.63 94.54 93.88 94.62 95.29 94.85 95.91 92.85 91.10 91.86 92.90 94.19 92.87 93.95
108 372 32 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 91.97 93.29 95.20 95.17 94.73 93.54 94.81 96.06 93.93 93.73 91.95 91.98 92.66 96.01 94.11 92.69 96.69 94.12 90.08 92.19 91.72 89.79 93.72 92.58 92.09
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.90 94.73 95.05 93.16 92.99 92.66 93.63 95.71 94.23 94.66 92.13 94.52 95.37 94.03 94.79 94.91 92.83 94.98 91.58 91.88 92.22 91.94 92.81 89.92 92.10
160 372 32 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.59 91.57 94.25 94.74 93.60 92.98 94.56 93.82 94.21 95.10 92.18 93.10 93.09 93.92 95.07 92.03 95.37 92.43 89.68 91.43 91.11 91.70 90.17 91.37 90.81
163 372 32 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.39 95.34 94.15 92.02 89.55 93.36 92.39 95.34 93.37 94.20 93.34 92.10 94.56 96.31 93.98 92.95 93.99 93.36 92.53 91.63 84.37 91.51 92.92 94.42 92.25
172 372 32 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 94.23 92.99 94.88 96.27 94.31 93.58 93.28 48.12 95.55 96.52 94.31 94.20 94.38 48.12 95.03 94.22 94.33 92.16 90.20 94.55 92.50 94.96 48.12 93.48 91.57
175 372 32 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 94.40 92.80 93.37 94.31 94.80 92.87 94.21 94.07 94.48 92.80 93.59 90.64 95.40 94.11 92.91 93.96 96.00 94.91 92.48 91.67 91.46 93.80 93.55 92.20 93.57
224 372 32 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 90.71 93.32 91.95 92.73 94.24 91.22 93.97 92.87 92.80 93.01 90.93 91.45 93.43 93.48 90.99 92.17 90.19 92.09 87.87 88.25 93.57 93.65 91.41 91.67 90.63
227 372 32 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 93.45 93.23 94.10 93.84 95.22 92.49 92.14 95.44 94.97 95.43 94.75 93.71 93.80 95.84 92.51 91.43 94.35 93.83 92.55 91.53 94.80 95.42 94.47 92.13 93.40
236 372 32 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 92.99 94.89 91.42 95.47 94.25 89.77 91.13 92.92 93.51 90.38 92.30 89.99 92.33 93.24 93.14 94.01 92.08 93.80 91.89 91.24 92.03 92.31 93.36 91.98 92.06
239 372 32 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 92.84 92.85 94.51 93.86 92.11 91.95 94.81 92.22 94.01 94.10 93.25 92.29 92.61 94.49 94.03 93.40 93.33 92.28 92.25 92.38 91.83 92.48 92.63 92.82 92.05
288 372 32 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 95.06 93.66 92.64 94.35 93.79 91.76 93.33 94.34 93.03 94.49 92.77 91.94 95.74 94.97 93.65 94.27 48.12 93.08 48.12 92.65 92.84 93.17 93.44 93.90 91.70
291 372 32 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 92.44 95.43 93.62 95.52 94.81 90.97 94.45 94.45 94.13 93.79 92.54 93.32 93.86 96.01 95.20 93.30 94.77 95.44 91.05 94.78 94.36 94.26 92.77 90.83 93.97
300 372 32 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 94.85 94.74 95.33 94.14 95.25 91.61 95.01 92.03 93.59 93.02 93.30 93.50 95.51 94.52 95.68 93.92 95.11 93.98 92.03 93.36 94.07 90.19 48.12 92.76 93.73
303 372 32 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 95.33 93.59 94.58 94.56 93.30 92.48 94.29 95.15 93.46 94.34 91.66 91.85 94.60 93.55 95.04 95.06 94.62 95.11 94.10 93.06 93.80 91.94 92.86 93.68 93.18
352 372 32 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 93.26 94.03 93.55 94.20 94.92 93.16 94.20 92.59 93.14 94.83 93.88 93.82 94.01 95.06 94.39 94.96 92.88 94.20 93.04 92.27 92.13 92.31 93.05 92.52 93.97
355 372 32 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 93.75 94.77 94.14 94.83 95.83 92.59 93.83 93.14 94.21 95.06 94.08 93.55 93.84 93.37 93.76 94.80 94.36 95.09 94.61 92.35 91.58 93.54 91.90 92.13 93.05
364 372 32 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 94.50 93.06 93.93 92.05 93.79 91.86 94.61 92.76 94.28 94.54 93.55 93.33 94.35 93.74 91.62 96.44 91.23 94.74 93.42 91.65 92.83 91.70 91.40 92.29 89.95
367 372 32 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 94.87 92.18 94.68 93.76 94.52 91.49 94.84 93.54 94.24 94.48 91.31 93.56 93.74 94.35 93.97 95.81 94.51 94.22 94.28 91.95 93.46 93.75 94.62 94.15 92.30
416 372 32 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 94.62 89.08 93.95 88.54 94.28 92.80 92.65 90.49 94.20 93.77 89.10 94.31 93.81 94.14 89.23 95.09 94.46 93.00 94.61 90.38 92.71 92.31 90.57 92.10 92.63
419 372 32 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 95.72 89.05 92.71 96.39 94.24 90.35 94.08 91.42 94.76 93.86 94.26 91.94 94.04 93.74 93.75 95.57 96.04 94.19 92.54 92.82 92.69 92.36 62.25 94.44 95.04
428 372 32 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 92.26 94.54 94.68 94.41 92.68 93.03 93.09 90.28 93.75 92.50 92.93 90.74 93.65 93.25 92.29 94.24 91.12 94.47 92.84 92.83 95.54 94.09 90.42 92.39 93.96
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 92.90 93.85 94.36 59.29 88.61 93.68 94.08 92.26 95.33 93.85 95.55 92.81 91.96 91.51 95.32 94.30 93.02 94.53 93.82 92.32 91.86 94.39 48.12 94.12 92.80
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 92.66 92.87 95.36 93.35 92.81 91.96 95.18 92.87 95.51 94.32 92.87 93.75 95.71 91.79 94.88 95.65 92.83 94.35 90.32 87.79 93.67 59.06 92.72 85.87 90.89
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 94.28 95.02 94.31 92.50 94.23 92.29 92.47 93.48 48.12 94.08 93.25 90.53 93.82 95.37 93.74 93.98 94.38 94.09 91.01 92.60 57.74 94.20 93.37 92.51 93.20
492 372 32 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 93.93 95.60 95.39 95.52 95.55 93.01 93.62 93.43 93.12 94.12 93.20 93.71 92.63 93.70 95.25 94.24 93.75 90.84 94.29 93.69 93.00 91.90 87.79 93.49 93.08
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 93.54 96.04 92.48 94.26 88.44 94.95 94.31 94.49 93.78 95.03 94.08 93.66 91.24 94.65 92.52 95.01 94.13 93.49 92.78 92.73 92.64 93.41 91.68 93.16 94.19
544 372 32 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 93.22 93.91 95.50 91.66 91.99 93.75 92.59 94.76 94.18 93.32 92.84 94.00 90.82 92.76 92.10 91.50 91.99 93.05 91.44 94.22 91.73 93.61 94.66 93.71 94.89
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 92.16 92.19 93.56 93.63 94.31 91.97 95.74 92.59 92.73 94.42 91.45 93.78 95.29 93.21 92.46 93.78 93.16 94.59 92.95 92.43 92.80 93.70 94.08 92.28 90.86
556 372 32 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 94.48 93.32 91.97 92.43 92.26 92.82 94.14 93.27 95.01 93.09 93.97 92.52 94.53 94.84 92.78 94.64 93.65 95.27 91.49 92.66 91.99 93.50 94.62 94.45 92.81
559 372 32 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 94.03 93.99 92.64 95.00 92.64 90.50 94.46 93.76 94.88 93.08 92.90 94.50 96.10 91.63 92.15 92.79 94.18 94.78 93.79 92.82 93.73 93.68 92.97 91.95 91.58
608 372 32 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 92.59 90.74 91.66 94.35 93.36 92.11 48.12 94.36 90.49 94.08 91.04 91.52 89.85 93.46 92.42 92.39 91.17 92.71 91.56 90.72 92.99 92.98 91.38 90.38 93.51
611 372 32 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 91.08 93.18 94.05 96.16 93.40 92.39 94.74 94.06 95.01 94.87 93.31 89.50 90.65 90.31 92.61 94.54 94.84 92.73 92.73 91.29 94.64 92.66 91.13 93.48 91.69
620 372 32 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 95.76 94.28 94.91 95.31 95.59 92.03 93.64 91.93 95.29 93.58 92.53 93.83 94.28 96.14 94.36 94.78 91.86 95.80 92.94 93.29 93.54 90.06 91.99 92.55 92.52
623 372 32 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 93.92 93.21 94.10 92.59 92.02 94.48 93.55 95.34 91.01 95.31 93.92 92.48 92.92 94.78 93.85 92.84 94.49 92.37 91.25 88.82 92.85 94.42 93.25 91.63 89.24
672 372 32 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 94.48 91.60 93.74 89.44 92.94 91.59 94.35 91.02 93.55 94.52 93.69 92.62 93.53 94.31 93.39 93.47 94.11 93.97 92.24 93.09 91.90 91.85 93.14 91.13 92.91
675 372 32 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 94.03 94.07 94.10 94.43 95.75 91.62 95.15 93.82 94.66 92.47 92.96 93.17 93.57 95.53 92.17 93.85 95.08 93.06 92.89 93.36 90.45 91.23 93.42 91.82 90.62
684 372 32 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 92.38 93.05 88.42 93.66 94.25 92.74 94.46 92.63 94.17 95.72 94.86 94.25 93.02 95.39 94.08 93.09 91.83 91.38 92.77 92.75 92.94 91.54 92.82 91.07 89.67
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 91.48 93.09 93.01 94.00 94.61 90.87 94.85 93.01 90.70 92.92 94.28 93.42 93.58 94.80 91.91 93.43 93.76 92.35 91.77 92.57 92.19 92.42 92.28 93.23 91.90
736 372 32 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 94.03 93.93 92.35 91.22 93.18 93.11 92.04 94.67 93.06 94.29 92.48 93.37 94.26 94.30 91.71 94.44 93.11 93.33 90.71 91.42 91.45 92.09 92.55 93.04 92.79
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 94.06 94.83 95.04 93.21 48.12 93.77 94.52 92.27 92.38 92.60 90.55 91.82 89.68 94.79 94.91 93.81 94.75 94.31 91.43 90.38 94.16 91.74 91.75 91.59 90.22
748 372 32 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 92.74 94.22 93.46 95.22 92.53 92.04 93.58 94.69 92.71 96.04 93.93 92.15 94.49 94.91 95.53 93.52 94.29 94.53 93.26 94.11 91.32 93.87 93.79 92.00 92.74
751 372 32 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.93 92.72 93.44 94.55 94.32 93.68 93.50 91.85 93.32 93.44 94.28 91.60 93.42 90.74 93.78 95.19 94.77 91.77 93.52 91.59 91.46 90.60 91.68 91.93 92.41
800 372 32 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 92.23 93.31 91.51 91.90 93.18 89.50 93.63 94.52 93.30 95.54 91.80 90.91 90.31 92.89 93.71 91.59 93.14 91.30 90.75 89.89 89.57 93.61 92.90 94.71 94.64
803 372 32 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 94.52 95.39 93.52 95.80 93.34 91.79 93.32 94.89 93.39 92.39 91.62 92.96 92.03 94.35 91.54 93.31 94.28 93.18 90.83 86.72 92.39 91.90 92.13 93.95 94.04
812 372 32 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 93.49 91.90 94.34 93.53 91.76 92.52 93.64 95.59 93.42 95.26 90.91 92.18 91.72 93.81 94.65 93.94 96.73 94.04 92.76 93.91 93.59 93.61 93.55 93.90 94.09
815 372 32 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 90.65 91.62 93.12 93.04 92.51 91.07 91.79 93.87 91.26 92.40 90.82 91.01 92.63 92.94 92.10 92.54 93.06 90.74 91.10 87.13 92.18 92.14 91.81 93.43 89.28
864 372 32 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 93.83 94.03 93.52 94.27 93.35 92.66 93.31 92.69 48.12 93.81 92.47 93.11 93.16 94.47 92.19 95.49 94.22 94.57 91.50 89.61 90.99 91.07 92.32 91.85 91.89
867 372 32 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 92.63 94.45 93.06 95.01 92.78 91.66 95.53 95.57 93.90 94.03 90.81 92.91 94.30 93.96 92.18 92.93 93.81 93.96 92.18 93.70 93.41 90.71 92.59 91.78 91.79
876 372 32 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 94.33 91.61 94.66 94.61 95.07 93.82 93.89 95.16 93.19 94.67 94.23 92.95 93.75 93.73 91.78 93.70 95.56 95.54 91.51 93.13 90.53 93.09 91.25 92.73 94.47
879 372 32 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 94.52 94.16 95.87 93.59 95.56 93.35 92.64 93.14 93.82 94.03 91.79 94.10 95.11 93.91 95.33 95.54 95.42 95.09 91.47 91.45 92.30 95.66 92.21 93.56 92.32
928 372 32 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 93.60 92.88 94.32 93.58 93.80 92.01 96.49 93.76 95.48 95.24 93.52 93.94 93.89 94.76 93.15 94.67 96.13 95.81 91.59 92.72 92.88 91.63 92.28 91.97 94.88
931 372 32 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 94.12 94.91 95.40 93.93 95.79 93.92 93.97 94.39 93.83 93.59 93.01 92.42 93.93 93.29 92.51 94.42 95.00 93.46 92.89 90.39 92.88 92.91 92.55 91.73 91.38
940 372 32 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 94.61 94.72 93.77 95.91 95.00 93.76 93.65 94.02 94.28 94.38 93.28 93.54 95.53 93.56 93.77 93.46 93.68 95.38 92.95 93.97 92.16 91.97 93.97 94.39 90.02
943 372 32 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 94.05 94.74 94.26 95.99 95.46 92.21 91.99 92.15 94.90 94.63 93.71 94.31 93.58 94.11 92.82 93.80 94.96 94.75 94.10 93.62 94.03 92.77 92.59 92.25 93.59
992 372 32 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 95.67 92.26 59.72 84.95 65.55 92.47 92.88 93.05 93.19 94.95 94.90 93.10 92.15 95.00 92.03 94.02 89.72 93.96 92.66 92.59 94.04 93.26 92.33 93.58 84.85
995 372 32 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 92.79 89.22 89.69 95.55 93.00 93.47 94.58 94.55 92.73 92.76 92.31 92.51 95.30 91.85 94.91 93.89 92.51 95.97 92.17 93.26 92.01 93.52 91.82 92.31 94.33
1004 372 32 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 91.86 95.29 84.18 94.45 92.94 94.52 94.70 94.07 95.07 94.59 91.68 90.98 85.84 95.43 79.41 94.98 95.00 95.47 93.42 94.24 94.58 94.80 92.39 92.88 87.90
1007 372 32 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 94.82 93.60 94.49 95.45 91.92 94.11 93.50 93.82 92.77 94.55 92.20 94.62 93.91 92.74 92.38 92.97 93.23 92.67 93.46 93.53 93.87 92.72 89.51 93.54 92.53
1056 372 32 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 94.49 58.74 94.03 94.77 91.86 90.91 95.34 92.94 94.22 93.72 92.89 92.00 92.31 93.54 93.14 93.06 94.18 91.88 93.47 93.51 61.54 93.20 94.62 90.74 91.61
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.50 94.48 95.72 94.29 94.50 91.88 93.05 95.51 94.71 93.83 92.54 93.35 95.01 91.01 93.83 94.80 92.96 94.11 93.33 90.77 93.56 91.70 92.99 85.10 91.60
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 94.53 91.72 94.30 92.52 95.20 92.52 95.13 94.01 93.54 94.36 91.32 93.27 95.72 92.35 90.60 95.61 94.72 94.00 94.06 92.88 92.84 93.28 94.04 93.79 93.02
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 95.49 93.46 95.25 95.08 94.41 92.63 93.14 94.79 93.76 94.43 93.12 93.58 94.06 92.81 93.52 94.17 93.53 94.77 93.31 92.63 94.76 93.19 59.16 91.71 92.85
1120 372 32 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 93.38 92.09 94.47 94.68 92.73 92.41 94.57 93.56 94.73 95.25 92.29 93.20 95.03 95.60 93.29 92.99 92.08 90.65 93.31 90.31 87.66 94.61 94.05 92.37 91.06
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 93.94 95.56 94.63 95.82 93.28 93.09 94.37 94.21 90.55 94.30 92.60 92.95 94.24 94.32 92.88 92.06 93.49 93.30 92.21 91.82 92.93 94.05 94.45 91.26 93.50
1132 372 32 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 93.87 93.05 93.47 92.53 93.71 91.57 93.25 93.79 94.58 94.08 93.85 92.04 93.97 92.73 92.58 94.04 93.84 92.58 91.50 93.09 95.14 94.08 94.81 94.49 93.47
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 92.27 95.17 93.79 93.81 94.48 91.81 94.70 92.62 95.45 92.59 93.04 94.49 93.38 93.11 91.70 95.94 93.29 93.75 92.62 93.04 93.96 94.52 93.33 91.51 90.11
1184 372 32 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 96.00 94.11 90.79 90.99 93.81 91.26 90.64 92.37 92.53 91.43 91.64 92.02 92.74 93.92 90.88 88.60 94.05 92.35 91.83 90.69 93.56 91.23 91.22 89.18 89.42
1187 372 32 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 94.64 93.71 92.24 92.90 96.68 93.87 93.10 93.66 94.24 92.12 90.48 90.54 95.56 92.01 91.89 92.30 94.93 92.83 92.77 91.03 91.48 94.22 92.97 92.65 89.55
1196 372 32 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 93.45 95.36 94.42 93.48 92.82 92.73 94.31 94.72 93.37 94.00 94.23 90.70 93.57 95.08 93.68 91.72 93.20 93.17 93.52 92.05 91.95 95.35 94.11 92.81 94.36
1199 372 32 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 91.76 95.23 91.76 95.32 93.03 91.34 94.61 95.55 94.88 93.19 91.45 92.70 90.99 93.32 94.02 95.00 84.26 94.07 92.76 93.71 93.09 93.64 93.40 90.05 93.13
1248 372 32 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 93.13 94.21 93.71 93.62 93.00 90.07 92.64 93.23 94.11 95.13 92.42 94.14 94.27 94.89 91.34 93.74 93.77 94.47 90.42 91.19 93.26 91.37 92.63 92.17 91.84
1251 372 32 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 94.44 92.24 94.31 94.50 93.83 93.81 94.41 92.04 94.51 93.42 92.52 91.59 92.63 95.50 94.72 91.14 94.57 94.16 91.56 90.30 92.28 91.72 92.78 92.49 91.60
1260 372 32 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 92.88 94.13 95.53 90.67 93.60 92.63 93.09 93.62 93.55 93.08 94.77 93.14 90.64 94.24 94.84 94.68 94.79 95.50 89.87 93.55 92.24 92.13 92.46 90.72 93.48
1263 372 32 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 92.24 91.36 93.46 92.89 94.91 90.76 93.33 91.58 94.13 94.35 94.40 90.79 94.05 94.40 93.47 89.56 95.03 92.40 91.81 91.88 92.44 93.02 92.71 91.01 91.50
1312 372 32 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 92.69 93.78 92.78 93.31 91.01 92.13 93.40 91.87 93.85 93.45 92.19 92.92 93.42 95.66 91.26 94.35 94.35 92.20 92.64 91.42 92.33 90.51 92.75 92.37 92.70
1315 372 32 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 92.99 94.02 95.40 94.12 95.78 92.23 92.53 94.95 93.80 94.45 92.82 93.72 90.93 95.02 93.86 95.74 95.97 95.05 94.23 92.61 93.05 91.20 92.27 91.57 93.67
1324 372 32 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.26 92.24 94.35 94.65 91.70 93.59 92.43 95.59 94.99 93.80 91.72 93.31 96.14 94.06 92.68 94.39 94.28 92.90 92.92 91.54 92.77 94.28 93.58 91.70 92.11
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 95.61 95.25 93.63 91.83 94.76 93.14 94.43 95.47 91.66 95.38 93.19 92.78 93.48 92.43 93.61 92.66 95.82 94.15 91.56 92.42 93.36 93.63 93.23 91.80 89.53
1376 372 32 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 92.86 94.31 91.89 95.37 93.91 92.25 92.94 93.19 93.43 96.00 91.70 91.75 95.09 92.76 92.94 91.08 91.83 93.81 89.01 89.94 93.65 93.18 94.92 93.94 92.19
1379 372 32 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 94.06 95.71 93.56 96.68 93.83 91.54 94.55 95.15 93.86 94.22 93.30 80.96 93.91 94.15 93.46 93.90 95.84 93.35 92.46 90.71 94.49 93.49 90.77 94.97 91.92
1388 372 32 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 92.33 93.32 93.46 95.36 93.09 93.24 92.52 91.54 94.67 93.67 93.24 93.15 94.01 93.39 95.40 94.16 94.45 90.74 92.93 92.55 94.74 89.67 93.02 91.13 93.53
1391 372 32 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 93.84 92.62 92.51 95.54 93.24 94.25 92.34 93.71 93.40 95.17 92.16 92.96 93.66 92.87 95.03 94.01 94.99 93.83 93.26 91.52 95.06 93.14 92.44 93.42 93.09
1440 372 32 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 93.12 93.72 93.16 94.74 85.22 92.12 94.60 92.23 95.45 94.49 92.12 91.59 93.46 95.04 93.66 93.89 94.47 90.54 92.70 91.79 92.80 92.96 93.11 91.20 93.05
1443 372 32 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 93.92 94.78 92.99 94.13 94.45 92.31 93.41 94.51 94.81 93.46 93.65 93.22 94.46 94.40 91.74 94.15 95.55 94.45 93.40 92.13 92.65 90.48 91.77 90.04 91.65
1452 372 32 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 93.27 94.93 94.69 95.47 94.97 92.47 95.77 95.05 95.43 95.00 91.42 93.87 93.71 94.40 93.23 94.56 95.02 94.28 93.28 91.94 91.90 91.85 92.83 92.95 91.62
1455 372 32 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 95.61 95.98 93.77 95.57 94.81 92.72 95.80 95.10 95.10 94.76 95.15 93.57 94.05 94.41 92.36 92.90 94.83 92.49 94.75 91.18 92.79 93.13 92.19 94.19 93.50
1504 372 32 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 93.84 95.55 95.06 94.12 92.32 93.82 93.79 93.99 95.57 94.44 92.95 95.60 95.64 94.16 95.03 94.99 95.18 96.05 92.68 93.14 93.44 93.37 92.30 94.64 93.46
1507 372 32 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 92.69 95.58 96.13 95.72 94.25 92.96 95.15 93.44 94.35 93.70 94.06 93.83 93.76 94.16 93.66 94.49 96.80 93.53 93.94 92.69 93.05 93.72 93.34 91.55 90.87
1516 372 32 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 94.23 94.15 96.01 94.96 95.46 92.45 94.39 93.12 95.32 93.90 94.10 93.46 93.68 93.84 94.45 93.76 95.54 95.13 93.59 93.49 92.23 92.55 93.41 92.00 94.18
1519 372 32 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 92.27 92.65 94.82 92.46 96.34 92.19 94.43 95.78 91.66 92.88 92.41 93.51 93.00 94.65 92.76 94.50 95.56 93.36 92.73 92.40 93.01 93.50 92.15 89.64 92.78
1568 372 32 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 95.15 71.94 93.46 94.14 90.25 93.09 92.57 94.05 89.97 94.60 92.39 92.36 93.55 88.88 95.59 90.92 94.67 91.46 92.23 94.46 92.83 92.94 93.56 92.60 62.34
1571 372 32 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 93.64 94.70 93.58 93.16 94.85 93.75 94.39 94.35 95.48 92.47 93.03 93.49 95.80 92.90 93.78 92.34 94.52 93.83 91.67 91.11 93.48 92.29 93.47 90.17 91.98
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 85.72 85.64 86.08 86.95 84.17 87.46 84.13 85.69 85.26 87.48 88.10 89.88 87.50 85.01 85.96 86.58 90.29 85.16 89.55 87.85 90.40 88.13 43.72 87.04 88.91
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 86.16 86.66 87.05 86.72 86.68 86.93 86.20 86.77 88.17 86.60 88.53 89.26 86.85 86.31 87.84 87.96 86.16 87.39 89.55 88.46 87.63 89.79 90.02 88.27 88.81
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 86.63 85.26 87.13 84.91 86.23 87.25 87.50 86.35 86.16 87.70 88.94 88.08 86.48 86.69 86.20 88.35 87.90 87.53 90.55 88.22 87.47 89.38 89.85 89.09 89.53
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.26 87.64 86.94 85.23 87.37 86.72 86.13 87.41 88.48 87.73 88.42 88.20 89.48 85.12 87.28 88.36 86.92 87.45 89.00 89.17 88.41 89.15 88.13 89.70 90.25
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 85.91 85.36 88.31 87.63 89.53 86.65 87.26 86.69 87.87 87.72 87.56 86.75 87.83 86.44 86.72 86.26 86.41 87.73 87.01 88.64 89.37 88.74 90.47 89.69 87.35
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.30 84.87 87.86 86.25 88.54 87.57 87.32 85.68 89.37 88.30 88.20 89.58 89.44 86.68 87.06 86.35 86.01 88.71 87.18 87.60 90.85 85.89 88.69 88.60 89.95
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 86.17 84.98 86.86 86.45 86.11 86.21 84.72 86.26 86.57 87.74 89.45 88.88 86.63 85.74 86.97 87.84 85.60 88.13 89.07 89.96 87.34 92.58 88.91 88.19 89.47
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 85.38 86.74 87.22 87.06 87.69 89.67 83.53 86.28 43.72 87.40 89.52 89.77 86.61 87.14 87.93 87.40 85.41 87.50 90.02 87.86 90.82 88.34 87.78 86.14 89.74
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.36 85.76 85.16 86.10 83.23 88.14 89.99 87.93 87.86 88.02 86.47 89.21 90.60 86.89 89.18 87.73 87.43 87.74 88.73 91.18 89.22 88.78 90.97 87.81 89.84
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 85.33 86.59 86.04 86.11 85.20 87.93 86.65 87.54 85.82 90.05 88.39 87.46 88.11 87.05 85.99 87.61 88.35 86.87 87.54 88.55 89.82 89.05 88.02 86.67 91.92
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 86.08 86.03 85.85 88.05 43.72 87.04 86.76 86.55 87.97 87.70 87.19 87.72 86.59 87.14 85.52 86.54 84.93 88.22 85.70 88.45 89.70 88.59 88.98 86.52 89.49
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.22 85.28 87.40 86.97 85.51 90.35 86.11 88.33 86.26 86.83 87.45 88.38 88.58 87.14 88.45 86.83 86.75 88.04 88.04 88.06 89.53 90.14 90.03 89.96 89.31
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.14 86.91 88.76 84.75 88.43 87.26 84.35 86.14 85.73 87.43 87.71 87.63 87.28 87.85 88.83 87.53 86.64 86.60 89.99 91.21 88.72 90.77 87.78 91.36 90.53
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 86.14 87.66 86.50 87.01 87.47 89.74 87.98 87.14 87.17 89.51 88.39 89.23 88.88 87.79 86.27 90.24 85.51 84.89 92.18 89.88 88.57 88.38 89.94 91.49 90.34
Size of the All data:  (98, 28)
Size of the Sig data:  (14, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
13 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 92.90 93.85 94.36 59.29 88.61 93.68 94.08 92.26 95.33 93.85 95.55 92.81 91.96 91.51 95.32 94.30 93.02 94.53 93.82 92.32 91.86 94.39 48.12 94.12 92.80
6 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 91.48 93.09 93.01 94.00 94.61 90.87 94.85 93.01 90.70 92.92 94.28 93.42 93.58 94.80 91.91 93.43 93.76 92.35 91.77 92.57 92.19 92.42 92.28 93.23 91.90
8 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.50 94.48 95.72 94.29 94.50 91.88 93.05 95.51 94.71 93.83 92.54 93.35 95.01 91.01 93.83 94.80 92.96 94.11 93.33 90.77 93.56 91.70 92.99 85.10 91.60
4 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 94.53 91.72 94.30 92.52 95.20 92.52 95.13 94.01 93.54 94.36 91.32 93.27 95.72 92.35 90.60 95.61 94.72 94.00 94.06 92.88 92.84 93.28 94.04 93.79 93.02
7 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 95.49 93.46 95.25 95.08 94.41 92.63 93.14 94.79 93.76 94.43 93.12 93.58 94.06 92.81 93.52 94.17 93.53 94.77 93.31 92.63 94.76 93.19 59.16 91.71 92.85
5 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.90 94.73 95.05 93.16 92.99 92.66 93.63 95.71 94.23 94.66 92.13 94.52 95.37 94.03 94.79 94.91 92.83 94.98 91.58 91.88 92.22 91.94 92.81 89.92 92.10
10 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 92.66 92.87 95.36 93.35 92.81 91.96 95.18 92.87 95.51 94.32 92.87 93.75 95.71 91.79 94.88 95.65 92.83 94.35 90.32 87.79 93.67 59.06 92.72 85.87 90.89
11 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 94.28 95.02 94.31 92.50 94.23 92.29 92.47 93.48 48.12 94.08 93.25 90.53 93.82 95.37 93.74 93.98 94.38 94.09 91.01 92.60 57.74 94.20 93.37 92.51 93.20
1 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 93.54 96.04 92.48 94.26 88.44 94.95 94.31 94.49 93.78 95.03 94.08 93.66 91.24 94.65 92.52 95.01 94.13 93.49 92.78 92.73 92.64 93.41 91.68 93.16 94.19
9 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 95.61 95.25 93.63 91.83 94.76 93.14 94.43 95.47 91.66 95.38 93.19 92.78 93.48 92.43 93.61 92.66 95.82 94.15 91.56 92.42 93.36 93.63 93.23 91.80 89.53
12 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 94.06 94.83 95.04 93.21 48.12 93.77 94.52 92.27 92.38 92.60 90.55 91.82 89.68 94.79 94.91 93.81 94.75 94.31 91.43 90.38 94.16 91.74 91.75 91.59 90.22
2 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 93.94 95.56 94.63 95.82 93.28 93.09 94.37 94.21 90.55 94.30 92.60 92.95 94.24 94.32 92.88 92.06 93.49 93.30 92.21 91.82 92.93 94.05 94.45 91.26 93.50
3 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 92.27 95.17 93.79 93.81 94.48 91.81 94.70 92.62 95.45 92.59 93.04 94.49 93.38 93.11 91.70 95.94 93.29 93.75 92.62 93.04 93.96 94.52 93.33 91.51 90.11
0 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 92.16 92.19 93.56 93.63 94.31 91.97 95.74 92.59 92.73 94.42 91.45 93.78 95.29 93.21 92.46 93.78 93.16 94.59 92.95 92.43 92.80 93.70 94.08 92.28 90.86
Size of the test data:  (14, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
480 372 32 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.49 7.89 8.50 6.90 6.70 5.75 10.46 6.61 8.94 6.58 3.42 4.87 9.08 6.05 7.91 7.81 7.23 6.22 1.25 -2.17 6.33 -33.52 3.81 -2.32 1.42 3
431 372 32 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.18 8.21 8.28 -27.66 4.44 6.22 9.95 6.57 10.07 6.37 7.45 2.93 4.46 6.50 9.36 7.72 2.73 9.37 4.27 4.47 1.46 6.26 4.40 7.08 3.89 1
1059 372 32 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.87 9.22 8.59 9.38 8.27 4.63 5.55 9.16 8.55 6.13 3.60 5.27 8.53 4.32 7.63 6.45 5.06 6.58 2.78 2.55 6.09 2.32 3.14 -3.99 2.07 1
1071 372 32 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.58 8.10 6.94 7.45 4.88 5.98 5.88 8.10 5.89 6.71 5.56 6.83 6.23 6.37 6.80 7.91 7.12 7.04 6.30 3.99 5.39 4.45 -31.31 2.02 5.50 1
483 372 32 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.90 8.28 7.09 5.44 6.54 2.62 8.94 7.20 4.40 6.68 3.73 0.76 7.21 8.23 5.81 6.58 8.97 6.59 0.99 4.74 -33.08 5.86 5.59 6.37 3.46 1
1327 372 32 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.28 8.66 7.59 5.72 9.56 5.21 7.78 7.93 5.84 5.33 4.80 5.32 5.37 5.38 7.62 5.05 7.47 7.28 4.02 3.87 3.54 4.58 5.21 5.13 -2.39 1
1135 372 32 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.13 8.26 5.03 9.06 6.05 4.55 10.35 6.48 9.72 5.16 5.33 6.86 6.10 5.26 2.87 8.41 6.65 7.15 2.63 1.83 5.24 3.75 5.55 0.15 -0.42 1
687 372 32 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.32 6.43 5.96 7.28 7.93 3.94 8.65 6.24 2.53 6.32 5.75 4.16 6.73 8.49 4.07 5.47 7.60 4.96 2.22 4.11 4.56 2.63 2.26 4.96 3.09 0
1068 372 32 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.27 4.08 7.36 7.29 7.83 5.80 9.00 6.60 5.06 6.63 2.90 5.07 6.24 7.23 3.32 7.25 7.80 6.55 5.06 3.71 4.43 4.13 5.91 4.09 2.77 0
111 372 32 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.60 9.86 7.19 6.91 4.45 5.09 6.31 10.03 4.86 6.36 3.93 4.94 5.93 7.35 7.73 8.56 6.82 6.27 4.40 4.28 1.37 6.05 4.12 1.32 2.15 0
495 372 32 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.18 10.28 7.32 8.16 5.21 6.81 4.32 6.56 5.92 7.01 7.61 4.45 0.64 7.76 3.34 7.28 6.70 5.75 4.05 1.55 3.42 4.63 0.71 5.35 4.35 0
739 372 32 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.98 8.80 9.19 5.16 4.40 6.73 7.76 5.72 4.41 4.90 3.36 4.10 3.09 7.65 9.39 7.27 9.82 6.09 5.73 1.93 4.46 3.15 2.77 5.07 0.73 0
1123 372 32 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.72 10.28 7.23 8.85 7.77 2.74 8.26 5.88 4.29 7.47 5.15 4.57 5.66 7.18 4.43 5.23 6.74 5.26 4.17 3.76 3.40 3.91 4.42 1.30 4.19 0
547 372 32 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.02 4.53 7.06 6.62 6.84 2.23 7.76 5.45 5.56 4.91 3.06 4.55 6.41 5.42 6.19 3.54 7.65 9.70 0.77 2.55 4.23 5.32 4.14 0.79 0.52 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_26 89.674286 1.023589
mAP_valid_zero_21 89.132143 1.165657
mAP_valid_zero_22 89.122143 1.502988
mAP_valid_zero_20 88.935000 1.186545
mAP_valid_zero_19 88.865000 1.668227
mAP_valid_zero_25 88.609286 1.707312
mAP_valid_zero_12 88.573571 0.967038
mAP_valid_zero_11 88.165714 0.845838
mAP_valid_zero_13 87.918571 1.309180
mAP_valid_zero_10 87.872143 0.921004
mAP_valid_zero_6 87.780000 1.271099
mAP_valid_zero_16 87.541429 1.053411
mAP_valid_zero_18 87.282857 1.096550
mAP_valid_zero_15 87.157143 1.145388
mAP_valid_zero_3 86.940000 0.979796
mAP_valid_zero_8 86.768571 0.803903
mAP_valid_zero_17 86.736429 1.411337
mAP_valid_zero_14 86.642143 0.863688
mAP_valid_zero_4 86.442143 0.971067
mAP_valid_zero_7 86.330714 1.730209
mAP_valid_zero_2 86.098571 0.938475
mAP_valid_zero 86.057143 0.927639
mAP_valid_zero_23 85.949286 12.198771
mAP_valid_zero_9 84.029286 11.664278
mAP_valid_zero_5 83.562857 11.597691


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_3 94.320714 0.940225
mAP_test_zero_16 94.293571 1.124815
mAP_test_zero_7 94.257143 0.911393
mAP_test_zero_2 94.161429 1.316989
mAP_test_zero_18 94.055000 0.675753
mAP_test_zero_10 94.055000 0.841891
mAP_test_zero_8 93.806429 1.246204
mAP_test_zero_17 93.762143 0.889712
mAP_test_zero_13 93.752857 1.774930
mAP_test_zero 93.522857 1.221521
mAP_test_zero_15 93.333571 1.394073
mAP_test_zero_14 93.298571 1.381826
mAP_test_zero_12 93.193571 1.034070
mAP_test_zero_11 92.855000 1.286030
mAP_test_zero_6 92.658571 1.022454
average_map 92.520229 1.243488
mAP_test_zero_19 92.339286 1.106592
mAP_test_zero_26 91.912143 1.423269
mAP_test_zero_20 91.875714 1.404015
mAP_test_zero_25 91.275000 2.690867
mAP_test_zero_4 91.196429 9.242248
mAP_test_zero_22 90.802143 9.186058
mAP_test_zero_21 90.620714 9.499128
mAP_test_zero_9 90.175000 12.214988
mAP_test_zero_5 90.053571 12.256997
mAP_test_zero_23 87.429286 14.500629
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
1068 372 32 0.1 32 0.0001 48 1.000000e-08 0.000000e+00 87.26 87.64 86.94 85.23 87.37 86.72 86.13 87.41 88.48 87.73 88.42 88.20 89.48 85.12 87.28 88.36 86.92 87.45 89.00 89.17 88.41 89.15 88.13 89.70 90.25
111 372 32 0.1 32 0.0010 24 1.000000e-08 1.000000e-08 84.30 84.87 87.86 86.25 88.54 87.57 87.32 85.68 89.37 88.30 88.20 89.58 89.44 86.68 87.06 86.35 86.01 88.71 87.18 87.60 90.85 85.89 88.69 88.60 89.95
495 372 32 0.1 32 0.0010 48 1.000000e-08 1.000000e-08 85.36 85.76 85.16 86.10 83.23 88.14 89.99 87.93 87.86 88.02 86.47 89.21 90.60 86.89 89.18 87.73 87.43 87.74 88.73 91.18 89.22 88.78 90.97 87.81 89.84
1123 372 32 0.1 64 0.0001 48 0.000000e+00 1.000000e-08 88.22 85.28 87.40 86.97 85.51 90.35 86.11 88.33 86.26 86.83 87.45 88.38 88.58 87.14 88.45 86.83 86.75 88.04 88.04 88.06 89.53 90.14 90.03 89.96 89.31
1135 372 32 0.1 64 0.0001 48 1.000000e-08 1.000000e-08 86.14 86.91 88.76 84.75 88.43 87.26 84.35 86.14 85.73 87.43 87.71 87.63 87.28 87.85 88.83 87.53 86.64 86.60 89.99 91.21 88.72 90.77 87.78 91.36 90.53
547 372 32 0.1 64 0.0010 48 0.000000e+00 1.000000e-08 86.14 87.66 86.50 87.01 87.47 89.74 87.98 87.14 87.17 89.51 88.39 89.23 88.88 87.79 86.27 90.24 85.51 84.89 92.18 89.88 88.57 88.38 89.94 91.49 90.34
Size of the All data:  (98, 28)
Size of the Sig data:  (6, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
4 372 32 0.1 32 0.0001 48 1.000000e-08 0.000000e+00 94.53 91.72 94.30 92.52 95.20 92.52 95.13 94.01 93.54 94.36 91.32 93.27 95.72 92.35 90.60 95.61 94.72 94.00 94.06 92.88 92.84 93.28 94.04 93.79 93.02
5 372 32 0.1 32 0.0010 24 1.000000e-08 1.000000e-08 92.90 94.73 95.05 93.16 92.99 92.66 93.63 95.71 94.23 94.66 92.13 94.52 95.37 94.03 94.79 94.91 92.83 94.98 91.58 91.88 92.22 91.94 92.81 89.92 92.10
1 372 32 0.1 32 0.0010 48 1.000000e-08 1.000000e-08 93.54 96.04 92.48 94.26 88.44 94.95 94.31 94.49 93.78 95.03 94.08 93.66 91.24 94.65 92.52 95.01 94.13 93.49 92.78 92.73 92.64 93.41 91.68 93.16 94.19
2 372 32 0.1 64 0.0001 48 0.000000e+00 1.000000e-08 93.94 95.56 94.63 95.82 93.28 93.09 94.37 94.21 90.55 94.30 92.60 92.95 94.24 94.32 92.88 92.06 93.49 93.30 92.21 91.82 92.93 94.05 94.45 91.26 93.50
3 372 32 0.1 64 0.0001 48 1.000000e-08 1.000000e-08 92.27 95.17 93.79 93.81 94.48 91.81 94.70 92.62 95.45 92.59 93.04 94.49 93.38 93.11 91.70 95.94 93.29 93.75 92.62 93.04 93.96 94.52 93.33 91.51 90.11
0 372 32 0.1 64 0.0010 48 0.000000e+00 1.000000e-08 92.16 92.19 93.56 93.63 94.31 91.97 95.74 92.59 92.73 94.42 91.45 93.78 95.29 93.21 92.46 93.78 93.16 94.59 92.95 92.43 92.80 93.70 94.08 92.28 90.86
Size of the test data:  (6, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1135 372 32 0.1 64 0.0001 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.13 8.26 5.03 9.06 6.05 4.55 10.35 6.48 9.72 5.16 5.33 6.86 6.10 5.26 2.87 8.41 6.65 7.15 2.63 1.83 5.24 3.75 5.55 0.15 -0.42 1
1068 372 32 0.1 32 0.0001 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.27 4.08 7.36 7.29 7.83 5.80 9.00 6.60 5.06 6.63 2.90 5.07 6.24 7.23 3.32 7.25 7.80 6.55 5.06 3.71 4.43 4.13 5.91 4.09 2.77 0
111 372 32 0.1 32 0.0010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.60 9.86 7.19 6.91 4.45 5.09 6.31 10.03 4.86 6.36 3.93 4.94 5.93 7.35 7.73 8.56 6.82 6.27 4.40 4.28 1.37 6.05 4.12 1.32 2.15 0
495 372 32 0.1 32 0.0010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.18 10.28 7.32 8.16 5.21 6.81 4.32 6.56 5.92 7.01 7.61 4.45 0.64 7.76 3.34 7.28 6.70 5.75 4.05 1.55 3.42 4.63 0.71 5.35 4.35 0
1123 372 32 0.1 64 0.0001 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.72 10.28 7.23 8.85 7.77 2.74 8.26 5.88 4.29 7.47 5.15 4.57 5.66 7.18 4.43 5.23 6.74 5.26 4.17 3.76 3.40 3.91 4.42 1.30 4.19 0
547 372 32 0.1 64 0.0010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.02 4.53 7.06 6.62 6.84 2.23 7.76 5.45 5.56 4.91 3.06 4.55 6.41 5.42 6.19 3.54 7.65 9.70 0.77 2.55 4.23 5.32 4.14 0.79 0.52 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_26 90.036667 0.437066
mAP_valid_zero_25 89.820000 1.464445
mAP_valid_zero_20 89.516667 1.528511
mAP_valid_zero_23 89.256667 1.246718
mAP_valid_zero_21 89.216667 0.903497
mAP_valid_zero_19 89.186667 1.743005
mAP_valid_zero_13 89.043333 1.106520
mAP_valid_zero_22 88.851667 1.698699
mAP_valid_zero_12 88.705000 0.750007
mAP_valid_zero_6 88.296667 1.443089
mAP_valid_zero_10 87.970000 0.909043
mAP_valid_zero_15 87.845000 1.143202
mAP_valid_zero_16 87.840000 1.369584
mAP_valid_zero_11 87.773333 0.746690
mAP_valid_zero_9 87.478333 1.368465
mAP_valid_zero_18 87.238333 1.343658
mAP_valid_zero_8 87.105000 1.023460
mAP_valid_zero_3 87.103333 1.230637
mAP_valid_zero_7 86.980000 1.927278
mAP_valid_zero_14 86.911667 0.996823
mAP_valid_zero_5 86.758333 2.042395
mAP_valid_zero_17 86.543333 0.682984
mAP_valid_zero_2 86.353333 1.214671
mAP_valid_zero 86.236667 1.379763
mAP_valid_zero_4 86.051667 0.913552


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_3 94.292917 1.041042
mAP_test_zero_13 94.009167 1.373906
mAP_test_zero_10 93.998333 0.755172
mAP_test_zero_4 93.960833 1.190626
mAP_test_zero_8 93.853750 0.970562
mAP_test_zero_17 93.666667 1.033204
mAP_test_zero_14 93.652083 1.329197
mAP_test_zero 93.597917 1.074021
mAP_test_zero_18 93.537083 1.414526
mAP_test_zero_5 93.393750 1.484417
mAP_test_zero_12 93.157083 0.991803
mAP_test_zero_15 93.125417 1.122567
average_map 92.835867 1.194375
mAP_test_zero_11 92.799583 0.748317
mAP_test_zero_2 92.492917 7.298858
mAP_test_zero_26 92.369167 1.310433
mAP_test_zero_19 92.331667 1.237883
mAP_test_zero_6 92.320417 0.990830
mAP_test_zero_7 92.237500 9.436777
mAP_test_zero_20 92.150000 1.382625
mAP_test_zero_9 92.150000 9.466575
mAP_test_zero_16 92.095833 9.453266
mAP_test_zero_23 92.007917 7.157574
mAP_test_zero_22 91.994167 7.105720
mAP_test_zero_25 91.879167 2.305935
mAP_test_zero_21 89.823333 9.499376


Summary using radar plot

Code
res1_valid['id'] = res1_valid.index.to_series().apply(extract_number)
res1_test['id'] = res1_test.index.to_series().apply(extract_number)



res_comb = pd.concat([res1_valid,res1_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res1_test = res1_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range1 = np.array(list(res1_valid['mean']) + list(res1_test['mean']))

categories = [str(i) for i in range(1,26)]

fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res1_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res1_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()




##############


res2_valid['id'] = res2_valid.index.to_series().apply(extract_number)
res2_test['id'] = res2_test.index.to_series().apply(extract_number)


res_comb = pd.concat([res2_valid,res2_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res2_test = res2_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res2_valid['mean']) + list(res2_test['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res2_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res2_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()

best_valid_bit_size_32 = round(res1_valid['mean'][0])
id_best_valid = res1_valid['id'][0]
best_test_bit_size_32 = list(round(res1_test.query('id == @id_best_valid')['mean'],2))[0]

best_valid_bit_size_32_mw = round(res2_valid['mean'][0])
id_best_valid = res2_valid['id'][0]
best_test_bit_size_32_mw = list(round(res2_test.query('id == @id_best_valid')['mean'],2))[0]




The results in this presentation are from two experimental designs:

The thresholding is based on fixed values between -1 and 1 on a step size of 0.1.

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
48 372 48 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 84.37 84.42 87.65 85.57 85.97 86.24 84.97 88.17 83.80 86.06 85.92 87.89 86.91 85.17 85.75 87.81 83.44 86.14 88.83 90.70 88.11 85.70 88.93 87.04 87.10
51 372 48 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 84.65 87.42 85.04 89.28 85.13 87.16 91.29 84.61 87.99 85.90 87.84 88.38 88.23 84.18 83.91 85.59 87.67 88.54 87.67 88.78 89.99 90.23 89.27 89.16 87.51
60 372 48 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 85.17 86.18 85.72 86.21 83.17 43.72 84.13 89.31 84.94 87.89 88.82 86.67 43.72 43.72 86.86 87.49 86.28 43.72 88.68 87.84 89.11 89.32 87.60 88.61 89.40
63 372 48 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 84.67 86.49 85.08 85.98 85.41 88.27 85.98 88.78 85.22 84.68 88.41 87.46 86.96 87.65 85.50 88.03 86.39 88.08 86.94 89.72 88.25 86.24 88.45 87.68 89.20
112 372 48 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 85.47 85.63 85.61 84.77 87.69 87.58 82.77 87.41 86.44 84.13 87.81 87.61 87.27 86.71 87.61 88.18 85.11 87.53 88.37 86.91 89.44 88.66 88.36 87.82 88.74
115 372 48 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 84.12 86.18 86.90 84.79 86.35 87.68 85.68 87.64 86.02 85.78 89.89 88.64 87.55 85.76 86.52 85.93 86.84 85.93 87.27 90.80 89.44 87.55 89.97 88.68 88.75
124 372 48 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 86.28 87.33 86.70 86.02 85.89 87.03 85.87 86.91 87.73 86.03 87.93 88.10 88.20 88.13 88.07 87.56 87.53 88.51 88.52 88.84 89.75 89.07 89.94 89.01 88.74
127 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.52 85.82 86.31 86.99 87.74 87.99 86.04 86.08 88.75 87.09 87.63 90.45 88.72 87.64 90.28 87.88 87.44 86.95 88.64 88.30 88.01 89.05 88.02 88.49 88.94
176 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 87.87 87.39 43.72 84.70 83.73 86.66 85.94 87.61 86.84 88.05 87.53 88.44 86.92 85.56 87.26 86.79 86.61 87.26 87.64 87.19 89.46 89.24 85.59 88.02 87.31
179 372 48 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 84.86 87.46 85.43 83.89 85.79 88.82 84.40 85.62 87.25 86.17 86.97 88.66 88.08 87.32 88.11 86.80 86.66 84.83 89.20 90.28 88.88 87.27 90.56 88.52 89.05
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.51 88.86 86.31 85.30 87.49 88.14 87.27 88.62 87.45 88.43 88.58 87.60 87.37 83.51 84.52 89.82 85.67 87.12 88.59 90.26 89.54 88.72 90.84 88.24 88.59
191 372 48 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.43 87.74 85.72 85.02 88.02 87.65 85.25 84.59 87.20 84.71 87.77 87.16 87.87 87.48 85.76 87.60 84.85 86.86 87.50 90.19 86.33 88.74 88.38 88.66 90.41
240 372 48 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 84.46 43.72 83.77 88.53 85.61 86.67 83.59 84.95 84.20 84.44 88.39 88.07 86.11 85.86 85.29 87.55 86.88 87.64 85.54 88.40 89.06 86.94 88.79 89.28 88.14
243 372 48 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 83.20 86.35 87.36 87.45 84.73 86.62 86.00 86.41 85.94 84.50 85.76 86.86 88.17 84.81 87.18 85.66 86.49 85.93 87.88 91.15 87.69 88.41 88.37 86.65 88.39
252 372 48 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 84.28 85.44 84.74 85.81 88.41 87.48 86.25 87.56 85.02 84.65 90.86 88.80 88.59 87.40 88.53 86.04 86.44 88.08 88.34 87.91 88.60 89.09 88.49 87.75 88.67
255 372 48 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 85.90 84.85 88.51 87.27 85.17 87.42 85.79 85.81 87.29 87.03 86.66 89.80 86.03 84.64 86.47 85.59 87.10 86.81 87.82 88.22 89.01 89.31 88.90 87.46 88.85
304 372 48 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 85.12 85.65 85.23 87.09 86.68 87.95 86.19 83.69 85.19 86.51 89.27 88.83 88.69 88.46 85.59 87.14 86.13 86.33 89.74 87.74 88.89 88.34 88.66 88.34 88.48
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 87.32 88.00 86.61 86.65 86.67 89.92 88.18 87.08 89.73 86.18 87.98 89.14 87.43 87.64 87.01 89.51 86.58 88.45 89.12 89.51 89.09 87.84 88.45 89.98 86.23
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 87.97 87.43 86.48 86.58 87.77 86.80 85.76 85.76 87.22 88.65 87.76 87.33 88.35 87.87 87.71 86.89 86.82 87.85 92.34 89.92 89.74 89.21 89.32 91.17 91.82
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 86.55 86.72 86.63 87.15 86.06 88.33 89.32 86.37 88.37 86.80 89.27 88.61 87.47 87.79 86.53 85.97 87.84 85.55 88.32 89.40 88.20 90.20 88.40 89.82 88.98
368 372 48 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 88.72 85.60 85.77 87.74 85.21 88.17 86.37 85.54 87.18 87.84 87.98 87.63 88.54 86.94 87.19 87.53 85.43 88.37 89.47 88.03 89.34 90.30 87.79 88.73 87.73
371 372 48 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 86.06 85.50 83.72 86.92 85.78 85.51 86.55 87.23 85.83 86.05 88.27 87.64 86.62 85.18 87.26 87.41 87.37 85.45 88.10 87.08 87.98 90.30 88.21 88.99 88.87
380 372 48 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 85.92 86.66 86.61 85.23 90.32 88.00 85.00 85.46 88.20 88.34 86.89 87.83 84.98 84.23 86.50 86.74 89.95 87.70 88.34 88.52 90.04 89.48 87.08 88.65 88.87
383 372 48 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 85.37 86.79 86.23 86.44 88.35 87.11 87.44 86.02 86.08 86.97 88.52 87.53 85.87 88.20 84.72 86.85 87.27 87.64 90.73 86.81 88.46 86.09 89.51 89.17 86.14
432 372 48 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 84.51 86.40 88.47 84.76 83.46 84.53 85.02 85.37 85.15 85.00 87.69 87.68 86.46 85.48 88.48 87.11 85.62 85.93 87.54 87.72 90.44 87.46 89.35 87.96 87.62
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.31 87.36 87.02 85.20 88.81 86.82 87.76 85.98 88.76 88.09 91.31 88.19 88.26 85.73 87.49 88.29 86.44 88.29 90.18 87.33 90.03 89.41 89.05 87.39 88.70
444 372 48 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 85.01 87.24 86.60 89.07 86.15 86.83 84.85 86.06 86.97 85.76 87.65 87.06 88.70 86.80 86.51 86.08 87.10 85.34 43.72 87.48 88.60 90.62 89.13 43.72 88.22
447 372 48 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 85.33 86.12 85.39 86.57 86.06 85.50 84.64 86.34 86.34 43.72 86.65 88.80 84.68 86.91 86.51 87.88 87.12 88.50 87.44 43.72 87.12 90.15 88.67 91.01 88.19
496 372 48 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 85.04 85.58 84.64 84.91 86.96 88.16 85.27 86.54 88.34 86.25 87.84 88.85 89.02 87.41 83.31 87.61 88.33 86.46 88.24 89.97 89.98 88.70 89.74 90.38 88.58
499 372 48 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 86.99 86.54 85.61 83.16 85.29 87.93 86.92 86.87 86.83 87.80 89.99 89.87 86.64 84.94 87.18 87.86 85.30 87.05 89.13 88.90 89.41 89.38 89.58 89.54 86.34
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 88.36 86.85 87.99 87.14 86.38 87.14 87.33 86.59 86.02 86.24 90.63 89.15 89.56 86.25 86.79 87.56 85.76 86.38 88.67 89.39 89.22 88.00 87.90 88.63 90.68
511 372 48 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.95 86.62 86.10 89.47 85.59 87.96 86.92 87.15 87.14 84.29 86.22 89.45 86.61 86.09 88.10 86.47 87.15 86.61 89.32 88.44 88.00 89.30 86.57 87.69 85.67
560 372 48 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 86.09 87.81 85.84 81.76 83.75 88.07 86.36 87.67 87.48 85.58 86.99 88.11 86.10 84.79 89.68 90.14 88.42 86.08 85.12 86.36 89.52 89.80 87.54 89.39 87.55
563 372 48 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 85.04 84.99 85.10 87.88 86.60 87.23 83.26 88.52 85.91 87.84 89.66 87.90 88.13 90.54 87.26 86.75 87.27 85.58 87.40 85.56 89.79 89.31 87.79 89.25 87.70
572 372 48 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 87.81 83.83 85.38 86.63 86.87 88.14 85.20 87.55 86.54 86.38 86.38 88.40 87.21 89.93 88.13 84.97 85.02 85.70 90.95 88.25 90.45 89.46 88.41 87.86 89.00
575 372 48 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 84.77 84.87 86.62 87.27 84.10 85.01 87.10 85.49 86.73 84.21 87.29 85.09 86.63 89.80 89.73 86.79 88.82 87.61 87.12 89.50 88.26 87.53 86.83 89.91 89.13
624 372 48 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 83.05 84.70 83.84 88.62 84.72 86.85 84.05 87.59 84.59 84.78 91.24 86.87 86.26 86.21 87.05 84.02 85.69 87.18 88.76 88.29 88.60 87.49 88.70 88.73 86.64
627 372 48 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 83.73 85.65 85.84 86.99 87.43 86.16 86.02 87.86 87.00 85.97 87.11 86.31 87.94 86.96 87.80 87.18 86.58 87.02 89.01 88.31 89.46 88.50 88.69 89.13 87.62
636 372 48 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 86.27 85.77 85.20 84.63 85.31 86.24 84.68 86.26 85.49 84.22 89.64 87.64 86.41 88.10 86.35 87.93 86.24 87.66 88.95 88.18 89.88 89.23 90.55 85.83 89.66
639 372 48 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 85.50 85.89 85.41 86.29 84.69 85.50 82.74 85.73 84.36 85.00 85.29 87.27 87.60 88.53 87.74 84.62 88.52 86.40 88.11 86.77 88.29 87.48 88.52 88.24 87.21
688 372 48 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 85.08 88.19 86.71 85.80 83.08 86.50 86.85 85.73 89.97 89.19 87.52 87.64 87.18 86.73 88.27 88.88 84.19 87.51 88.80 87.71 88.44 88.39 87.69 89.14 87.26
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 87.37 86.62 87.45 86.35 88.49 89.31 86.41 90.66 87.17 85.77 89.63 88.47 87.05 88.37 87.99 87.58 86.36 86.24 90.28 89.40 88.24 93.05 89.50 90.33 89.35
700 372 48 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.83 86.92 86.94 86.14 85.74 86.88 85.93 86.62 87.20 88.25 90.36 86.18 86.23 89.14 86.58 87.65 85.80 87.19 89.48 88.04 88.21 88.63 89.25 89.88 88.88
703 372 48 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 87.54 87.53 87.10 87.99 86.91 86.16 90.15 86.02 88.54 87.97 88.59 87.70 86.10 85.65 87.19 87.16 85.86 84.95 89.60 89.75 88.66 89.09 88.28 88.05 89.55
752 372 48 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 85.57 84.99 84.71 82.51 82.91 86.61 87.50 86.39 85.17 85.35 86.76 87.51 88.66 87.29 86.70 85.17 85.33 87.92 86.49 89.74 89.05 89.05 86.93 87.63 87.29
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.15 89.30 86.12 86.29 88.10 87.95 87.62 89.40 88.18 85.85 89.19 89.72 89.27 87.64 85.49 85.87 87.27 87.85 89.46 89.46 90.70 89.08 87.53 89.91 90.16
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 86.12 85.42 86.33 84.78 88.09 87.22 87.28 87.74 85.96 86.23 88.16 87.13 86.26 86.46 88.10 88.81 89.16 87.10 89.09 89.77 90.97 88.25 89.53 89.59 88.09
767 372 48 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 85.86 85.33 86.08 85.98 83.76 87.78 84.47 87.02 87.35 87.72 87.75 86.65 86.19 87.94 86.27 86.14 85.91 85.51 87.57 87.89 88.46 88.38 89.50 89.85 87.65
816 372 48 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 84.36 84.02 84.57 87.47 85.15 85.02 86.34 85.41 86.41 85.90 85.99 88.65 87.32 88.63 88.75 87.31 86.70 87.08 90.06 87.93 88.67 87.40 88.91 87.91 87.37
819 372 48 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 84.36 87.86 85.14 85.43 84.97 89.72 84.86 85.11 85.00 85.77 86.41 87.04 85.82 86.23 87.94 87.28 85.87 87.26 89.45 87.46 88.38 88.79 87.67 88.68 87.86
828 372 48 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 84.71 85.82 86.69 85.40 84.41 85.97 83.40 88.34 86.22 85.55 89.19 88.67 87.75 87.90 86.67 87.44 86.60 86.44 90.53 90.61 88.98 90.52 88.76 89.39 87.84
831 372 48 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 84.89 85.57 84.12 87.58 86.37 87.47 85.60 87.97 85.38 85.88 88.36 86.09 88.08 86.74 89.27 86.85 86.32 84.74 89.76 87.66 87.81 88.76 88.69 88.45 88.46
880 372 48 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 87.46 85.24 85.72 84.48 86.71 87.90 83.03 86.56 89.26 85.85 88.76 86.00 84.68 85.00 87.60 89.52 87.10 87.67 88.30 87.73 88.88 87.08 87.37 89.04 89.72
883 372 48 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 88.07 43.72 88.33 87.20 86.55 88.21 86.29 87.40 87.02 87.62 86.36 89.27 85.97 84.64 85.97 88.16 87.88 87.46 87.72 87.96 87.05 43.72 89.48 87.88 88.43
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 87.05 87.43 87.24 85.47 86.21 88.10 86.70 88.84 88.14 87.37 89.02 87.30 88.20 86.63 86.45 88.11 86.91 86.36 88.77 89.88 88.52 88.89 89.66 88.68 89.26
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 85.61 88.38 85.63 87.49 87.86 87.52 85.12 86.15 86.89 87.75 88.74 87.45 89.02 87.14 87.37 88.88 86.57 87.43 88.44 89.52 89.36 89.52 89.02 90.31 88.79
944 372 48 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 84.95 85.42 89.58 85.96 86.85 87.58 85.58 88.36 87.00 87.50 87.48 86.34 88.44 86.64 86.41 87.80 87.20 85.54 87.89 87.71 90.06 88.93 88.92 89.84 88.10
947 372 48 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 87.03 86.18 87.22 88.15 85.78 86.80 87.65 88.55 86.23 86.79 87.56 87.14 86.49 84.95 88.11 84.86 86.21 86.37 87.36 89.67 90.61 88.74 88.60 87.05 88.93
956 372 48 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 87.37 86.60 86.20 85.30 86.01 86.60 88.60 88.63 87.27 89.30 88.91 89.14 85.91 87.57 86.11 87.39 86.08 86.88 88.80 87.47 86.84 89.41 87.78 87.90 87.21
959 372 48 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 86.09 85.02 86.14 86.08 86.35 88.06 86.17 86.27 86.05 87.38 86.54 89.28 87.35 85.70 90.59 87.77 83.68 87.06 89.17 88.56 90.30 89.12 88.87 86.65 88.18
1008 372 48 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 85.15 86.48 85.61 86.40 84.01 87.14 86.54 86.08 87.68 86.06 88.30 91.42 87.89 86.24 88.14 87.69 86.93 87.95 90.18 88.18 89.10 88.27 87.06 89.62 86.04
1011 372 48 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 86.04 87.35 86.65 85.12 84.76 88.26 85.97 86.47 86.84 86.10 86.38 84.70 86.61 84.24 85.17 86.73 86.67 86.41 88.00 88.04 88.43 89.63 88.78 90.01 88.08
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 85.60 87.07 86.35 90.41 85.34 87.96 85.23 87.80 86.79 89.02 88.58 87.93 86.76 85.46 86.77 87.08 87.41 87.66 88.73 89.30 89.08 89.63 88.91 89.66 89.09
1023 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 84.33 86.79 87.50 88.68 85.99 90.55 88.03 86.45 87.50 88.57 87.07 89.91 87.59 87.17 86.97 88.85 88.96 86.76 88.03 87.13 89.36 88.05 90.22 87.84 87.12
1072 372 48 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 83.53 84.73 87.18 87.12 88.77 87.70 85.51 87.19 86.87 87.82 87.71 88.13 87.78 86.70 85.34 85.73 85.44 86.75 89.10 90.45 89.93 87.54 87.95 89.17 88.75
1075 372 48 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 86.26 85.85 84.84 86.26 88.01 87.98 87.68 86.68 88.53 86.34 87.79 88.27 86.22 86.80 86.06 88.91 85.12 86.67 89.90 88.34 89.77 88.40 87.84 87.58 89.55
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 88.63 88.33 87.15 86.58 89.23 88.69 88.24 87.40 89.00 86.43 87.32 89.68 87.52 88.24 88.39 89.32 85.88 87.85 88.06 89.80 89.57 88.35 87.96 89.94 90.95
1087 372 48 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 86.25 85.62 85.75 85.22 85.81 85.45 86.13 86.51 87.22 85.84 89.21 87.02 88.03 86.46 86.58 88.04 86.46 86.63 88.43 89.74 89.52 88.51 87.68 87.98 88.47
1136 372 48 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 83.47 86.75 85.57 86.01 86.37 87.40 85.58 87.94 84.60 86.86 88.62 84.94 87.08 88.28 85.16 88.70 87.89 87.20 87.70 86.76 80.84 89.24 88.68 89.15 89.91
1139 372 48 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 87.72 84.12 86.73 84.93 86.78 88.55 83.86 88.54 87.94 86.19 86.27 85.77 84.95 87.96 86.55 89.47 86.41 85.77 87.02 87.95 85.83 88.20 88.47 88.36 87.31
1148 372 48 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 86.43 86.40 86.17 84.73 82.01 84.73 85.71 85.16 88.02 86.65 89.17 89.33 84.82 84.24 84.70 87.00 86.30 85.23 87.22 87.66 87.50 90.76 87.77 90.48 87.81
1151 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.12 86.48 86.93 88.27 84.68 87.09 87.67 89.66 86.65 87.59 87.84 88.95 88.64 86.36 86.17 87.12 85.48 86.99 87.89 88.08 89.58 89.54 89.82 89.26 88.31
1200 372 48 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 84.90 85.14 84.62 89.46 86.80 86.42 84.27 86.51 85.60 84.20 87.79 88.01 85.06 85.63 86.10 85.76 86.94 85.40 87.94 87.24 89.25 89.08 87.66 87.89 87.83
1203 372 48 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 85.27 86.46 85.89 88.30 86.35 86.84 83.43 86.38 87.09 84.70 87.54 88.71 86.33 86.29 88.93 87.11 87.61 86.55 87.78 89.74 89.06 88.76 88.40 87.78 89.36
1212 372 48 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 85.84 87.15 85.72 86.99 85.41 86.96 85.94 87.46 88.25 85.67 89.45 87.81 86.63 86.33 86.62 86.05 86.86 85.80 88.13 89.72 88.44 87.37 88.47 88.98 88.43
1215 372 48 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 85.49 85.56 85.98 85.17 84.33 85.25 83.02 88.34 84.44 84.82 87.18 88.45 89.29 86.30 86.43 85.89 86.59 86.73 86.88 86.63 89.42 86.02 88.02 88.55 88.80
1264 372 48 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 85.46 86.87 84.17 84.40 87.41 88.03 83.49 89.10 87.16 87.79 87.60 88.36 86.54 86.21 85.88 88.16 87.52 86.49 88.10 90.70 90.11 88.61 86.91 88.76 89.37
1267 372 48 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 85.03 86.24 86.07 86.98 87.28 86.84 86.90 85.85 86.61 88.16 88.75 87.78 87.06 89.04 87.60 85.37 88.43 86.77 88.10 88.62 89.63 90.12 89.48 88.97 89.07
1276 372 48 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 85.77 85.66 86.80 87.11 87.92 86.57 87.60 87.04 86.05 85.70 89.08 87.74 86.80 86.59 86.92 86.85 88.12 89.60 88.65 87.62 89.62 88.86 86.21 89.44 91.27
1279 372 48 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 86.25 88.00 85.87 84.34 87.64 88.13 86.68 85.15 87.88 86.87 87.75 88.27 87.50 84.66 87.62 87.38 87.51 85.29 88.81 88.20 89.08 89.29 89.27 88.87 89.38
1328 372 48 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 85.37 88.49 86.96 62.09 86.75 86.69 87.16 84.87 87.76 85.66 86.82 89.57 88.30 87.45 87.43 87.28 87.28 84.63 87.78 88.95 87.94 88.28 89.42 86.09 83.52
1331 372 48 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 86.30 84.51 86.39 85.87 86.59 86.70 85.90 85.50 91.28 86.84 87.32 87.86 87.92 87.03 87.35 87.70 87.00 87.01 88.53 88.61 89.22 87.05 88.47 89.03 88.92
1340 372 48 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 85.97 85.67 85.28 87.44 85.37 88.08 85.43 89.58 85.91 86.83 86.50 87.22 86.56 88.91 87.92 88.68 86.06 86.59 89.28 88.15 89.80 87.90 86.29 89.23 87.47
1343 372 48 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.44 87.23 86.07 87.72 86.62 88.09 86.78 88.11 85.99 86.84 90.48 88.72 89.36 87.62 85.15 87.53 84.99 86.56 87.94 88.46 89.38 89.17 87.75 88.93 89.26
1392 372 48 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 84.15 87.22 86.42 86.33 86.04 86.82 87.21 89.18 89.37 85.79 86.46 88.47 87.49 86.19 88.18 87.74 87.13 86.39 87.37 87.13 90.22 89.20 89.60 89.99 90.32
1395 372 48 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 84.90 87.43 86.06 88.63 84.69 87.60 85.34 85.84 84.66 86.61 88.77 88.96 87.36 83.22 86.62 86.52 85.22 86.92 90.55 88.74 88.30 89.61 88.27 89.12 88.43
1404 372 48 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 86.09 84.80 86.33 89.11 84.81 87.82 85.70 85.69 85.95 86.25 88.26 87.35 86.34 86.18 86.19 88.62 85.09 89.40 87.06 88.53 87.93 87.74 89.14 88.35 87.80
1407 372 48 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 84.54 86.02 86.79 84.80 84.56 86.47 86.58 90.43 85.35 85.22 88.05 88.21 87.34 87.74 90.88 87.82 87.15 86.11 87.67 87.38 90.00 89.06 89.84 87.86 90.23
1456 372 48 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 88.13 88.06 85.81 86.94 84.89 84.96 85.72 90.37 84.09 85.97 87.62 89.66 86.74 86.67 85.44 86.64 85.54 86.49 88.80 89.12 88.56 89.69 88.76 90.50 87.33
1459 372 48 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 86.47 87.77 87.14 85.97 86.59 86.68 86.36 86.79 86.10 87.53 89.54 86.05 86.22 87.83 85.83 86.73 85.96 87.43 87.78 87.72 90.11 89.91 91.01 88.81 89.62
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 87.90 86.66 86.71 85.40 87.97 89.21 86.53 84.85 88.66 86.64 88.41 87.14 87.23 87.33 87.33 88.78 88.90 86.67 91.27 87.59 89.03 88.67 89.27 88.59 89.84
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.25 86.75 87.45 90.66 84.77 86.47 88.10 86.77 84.65 86.68 88.72 89.57 89.73 83.16 86.04 88.15 85.51 89.01 88.81 91.07 89.49 89.02 90.18 88.63 87.06
1520 372 48 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 85.42 84.39 85.96 87.60 86.58 88.40 86.99 87.23 86.26 87.82 89.02 87.02 87.56 84.89 86.15 88.15 88.18 87.59 87.49 88.21 89.23 87.80 88.26 89.92 89.07
1523 372 48 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 87.12 85.91 85.31 87.08 90.59 85.70 86.90 86.19 85.99 86.88 86.40 91.51 88.11 88.10 86.45 86.53 84.76 86.15 91.44 88.36 86.39 88.99 89.52 89.48 87.58
1532 372 48 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 85.27 87.21 85.21 85.60 86.48 87.50 84.60 88.30 85.58 87.16 87.38 87.89 85.67 88.23 84.52 89.38 86.06 86.81 87.51 89.28 89.17 87.09 89.28 87.55 88.41
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 85.43 87.50 89.00 86.80 86.12 86.31 86.95 85.54 86.01 86.10 87.92 88.16 87.81 87.67 86.52 87.75 90.14 87.07 89.75 92.23 88.93 88.88 88.37 88.85 88.22


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
48 372 48 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 91.58 91.62 90.60 91.84 92.42 91.43 89.10 90.55 93.86 91.29 91.54 90.19 92.37 93.31 91.47 80.21 92.45 91.87 89.73 89.60 92.03 91.42 90.07 92.53 89.79
51 372 48 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 93.70 92.93 96.39 91.25 94.47 92.51 91.80 94.66 94.78 93.42 91.22 92.95 93.33 94.01 92.98 92.71 94.84 80.75 94.13 90.11 94.24 92.75 91.88 92.27 92.48
60 372 48 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 92.00 93.03 93.99 92.90 94.03 48.12 94.01 93.48 93.17 92.60 93.85 88.37 48.12 48.12 93.08 93.65 92.05 48.12 94.11 91.85 92.71 92.83 90.16 90.56 93.19
63 372 48 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 90.60 92.37 95.02 92.79 91.06 92.18 92.92 92.98 91.45 92.75 91.85 90.47 93.41 91.61 93.15 93.40 92.82 93.95 94.36 92.70 92.59 93.25 92.85 91.94 87.51
112 372 48 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 92.44 94.38 95.75 90.82 93.68 92.79 94.79 94.09 94.57 94.69 93.86 91.75 93.69 93.47 94.38 93.29 94.42 92.92 92.96 93.74 93.24 92.23 91.82 92.55 92.65
115 372 48 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 92.03 92.70 93.99 94.70 90.91 92.70 92.25 91.89 93.81 92.53 83.87 93.75 92.15 92.85 92.80 93.54 94.35 94.14 93.52 90.31 92.20 92.19 92.47 93.70 91.60
124 372 48 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 90.62 94.13 91.43 93.95 94.54 91.67 93.74 94.93 92.50 93.49 89.82 91.57 94.90 93.45 92.72 92.39 93.24 93.59 93.62 91.31 91.73 91.70 91.81 93.05 93.10
127 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.52 92.37 94.59 93.73 95.07 92.57 93.22 92.69 95.96 93.10 94.14 90.79 94.15 96.09 89.53 93.70 94.96 93.76 94.41 92.78 92.75 92.36 89.65 91.54 89.07
176 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 93.70 90.95 48.12 92.95 93.50 90.97 93.76 95.68 93.71 95.25 94.35 92.90 93.59 95.18 93.97 93.11 91.94 93.33 92.56 92.84 89.16 93.13 91.27 92.25 91.75
179 372 48 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 93.66 92.32 94.43 94.71 92.63 93.39 92.24 93.39 93.47 94.76 89.34 94.43 95.83 95.05 93.45 93.78 95.34 92.45 92.73 91.63 91.97 93.52 94.42 91.17 93.80
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 93.94 92.61 92.99 91.60 93.62 92.79 94.98 94.40 93.57 94.08 91.30 89.75 94.38 91.24 94.74 93.57 95.51 94.78 93.46 89.55 93.61 91.50 94.72 92.09 88.73
191 372 48 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 95.42 95.80 93.76 94.71 95.14 93.02 94.69 92.30 94.45 92.94 94.54 92.14 93.05 94.54 95.92 91.75 95.28 92.56 91.51 90.64 93.44 92.09 93.72 92.65 92.95
240 372 48 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 90.96 48.12 94.03 93.08 91.64 90.96 91.65 91.53 91.86 91.29 91.76 91.56 92.88 93.73 92.81 92.75 90.85 93.92 90.00 92.52 91.03 90.96 94.01 91.25 89.03
243 372 48 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 93.81 91.79 93.14 93.99 93.20 92.05 94.15 93.86 92.52 92.82 92.72 89.72 93.65 92.38 93.96 94.18 93.29 94.93 91.81 91.19 92.14 93.25 94.13 95.56 92.25
252 372 48 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 92.25 95.66 94.36 95.33 95.86 92.08 92.57 95.31 94.64 93.91 94.39 91.82 93.59 94.23 94.43 94.67 94.46 95.45 92.45 91.54 94.64 92.98 93.86 93.87 93.68
255 372 48 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 92.15 91.41 93.38 94.47 94.86 93.85 91.40 94.88 93.27 93.70 93.96 93.50 94.18 94.24 94.79 94.56 95.88 95.06 93.59 91.80 92.36 91.66 93.50 94.81 89.76
304 372 48 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 94.39 91.86 95.35 94.40 93.03 93.89 94.48 95.41 94.43 94.78 92.87 90.67 94.49 93.65 91.14 93.81 92.21 95.02 90.78 91.64 92.54 94.28 93.36 92.92 90.10
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 93.71 94.56 90.96 94.57 92.55 89.98 95.28 94.57 94.32 93.75 93.04 90.96 95.36 93.09 92.27 91.81 95.07 94.65 90.15 92.35 93.34 91.22 93.76 91.11 91.68
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 93.60 95.85 93.82 95.20 93.83 91.42 96.37 93.65 94.94 93.29 92.14 94.10 92.97 94.34 92.59 93.16 95.08 92.05 92.36 91.99 93.15 92.27 92.37 93.10 92.66
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 93.95 91.41 90.78 95.00 94.22 91.58 94.07 94.24 93.00 93.35 92.59 93.98 94.57 94.77 94.41 95.55 91.64 91.90 92.53 93.35 93.70 93.71 92.50 92.18 91.75
368 372 48 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 92.53 93.44 94.70 92.84 95.76 92.27 94.68 95.18 94.72 94.23 94.90 93.61 94.64 93.79 94.13 93.22 94.98 94.27 93.28 93.46 91.82 92.08 92.69 93.92 92.03
371 372 48 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 93.98 93.96 94.47 95.43 95.80 91.97 93.27 94.81 95.34 94.66 94.09 93.52 94.16 90.60 94.27 94.04 95.23 93.80 93.41 92.58 94.69 92.20 94.59 95.00 91.01
380 372 48 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 94.19 92.43 93.25 93.59 92.99 92.56 94.36 94.41 93.87 93.41 91.64 92.36 96.94 97.09 92.70 93.87 93.60 95.72 92.72 92.77 92.08 90.59 93.41 92.03 91.17
383 372 48 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 93.60 94.87 92.87 92.39 95.03 92.02 95.61 93.62 93.62 95.40 92.59 92.94 92.18 95.36 94.81 93.19 94.01 92.38 90.71 91.57 94.58 93.22 91.92 93.74 93.86
432 372 48 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 91.07 94.71 92.42 94.42 95.04 92.94 94.57 91.32 93.05 96.23 91.71 93.55 94.17 94.79 94.08 82.59 92.58 92.63 93.91 89.93 88.70 93.70 91.83 91.76 91.87
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 93.23 95.25 92.71 93.39 93.96 91.78 92.47 93.87 94.74 94.94 91.90 94.74 93.30 92.93 94.05 95.55 94.67 93.63 92.65 89.88 94.25 92.06 92.78 91.43 93.27
444 372 48 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 93.74 94.99 93.71 94.27 94.21 90.25 93.48 95.96 94.52 93.09 93.13 91.27 94.34 94.68 94.15 92.87 95.54 94.53 48.12 92.69 93.11 91.15 93.79 48.12 92.48
447 372 48 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 94.66 94.75 95.28 94.68 95.47 92.66 92.99 95.54 94.74 48.12 93.80 93.64 95.51 94.56 96.34 93.96 96.49 94.30 93.97 48.12 94.90 91.73 92.46 92.90 91.84
496 372 48 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 92.61 92.80 93.05 92.67 94.01 92.72 92.56 94.55 94.03 93.62 91.08 91.52 93.37 93.29 93.92 93.75 95.30 94.09 93.52 92.41 93.15 93.93 94.48 93.48 93.50
499 372 48 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 94.34 95.78 94.15 93.46 93.07 92.47 91.65 94.64 94.42 93.42 84.41 93.52 92.33 94.38 95.28 92.35 95.92 92.18 91.93 91.92 92.33 88.09 93.65 93.21 93.06
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 94.21 94.96 92.77 94.52 93.78 92.43 94.31 94.22 95.81 94.24 91.99 93.11 92.54 94.26 94.06 92.77 96.25 94.59 92.83 92.40 93.52 93.36 93.92 94.77 92.14
511 372 48 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 94.77 93.07 94.33 92.96 94.80 91.20 94.34 95.39 91.57 93.71 91.74 93.61 91.22 94.64 93.13 93.02 93.54 95.61 91.53 91.44 92.47 92.50 91.91 93.54 93.24
560 372 48 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 92.51 94.13 94.51 90.96 89.19 92.29 92.28 93.77 91.58 95.01 92.32 93.22 90.75 94.01 94.47 93.92 94.55 92.71 92.37 92.89 91.73 92.24 91.62 92.16 92.33
563 372 48 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 94.19 93.91 93.33 93.46 94.17 92.55 94.38 94.87 93.05 93.92 92.17 91.73 93.64 93.60 94.88 93.83 94.96 95.33 91.84 93.36 92.72 93.65 92.98 92.09 93.21
572 372 48 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 95.76 95.70 91.10 91.46 94.66 93.07 93.93 94.90 92.85 94.68 92.22 93.05 93.83 95.20 93.44 94.59 95.16 95.17 92.82 93.02 92.68 92.78 91.80 93.41 90.80
575 372 48 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 93.78 91.31 92.90 92.81 93.79 91.54 94.62 92.19 92.10 93.96 92.87 92.64 94.05 95.83 93.04 93.76 93.98 93.56 91.03 90.73 91.00 91.78 91.29 93.52 90.69
624 372 48 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 92.40 90.41 93.13 91.29 91.58 91.11 93.21 94.26 93.03 90.60 90.34 93.16 90.22 94.10 93.52 89.23 93.73 89.78 90.95 88.62 93.53 92.84 91.92 91.78 89.56
627 372 48 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 92.00 92.85 92.09 92.59 91.93 91.53 92.61 94.66 93.31 95.27 92.39 92.57 93.60 94.50 93.26 94.14 94.52 93.23 90.41 86.70 93.03 90.14 92.99 88.84 90.64
636 372 48 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 93.32 94.66 94.81 92.21 86.66 92.90 91.83 92.08 91.71 93.02 91.60 88.86 94.58 94.32 93.89 91.85 93.65 91.05 92.25 90.11 92.50 94.72 90.56 92.77 92.93
639 372 48 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 92.01 94.34 93.75 92.05 91.63 94.12 92.05 90.84 93.65 92.07 93.80 92.41 95.88 92.26 92.91 94.53 93.29 91.61 91.36 89.68 91.05 93.34 91.88 93.45 91.99
688 372 48 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 90.48 92.91 91.19 95.69 91.60 91.81 90.65 93.99 90.88 91.47 89.48 91.48 92.85 93.57 91.31 93.14 93.93 89.04 92.10 92.11 92.02 92.79 92.79 92.78 90.33
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.56 93.20 95.32 93.18 93.09 91.37 94.42 93.38 94.33 90.86 93.95 90.55 92.68 93.35 93.55 93.65 96.17 92.59 91.94 93.39 91.20 91.64 92.62 91.37 93.61
700 372 48 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 94.65 92.82 93.88 93.42 90.52 92.30 92.20 91.43 94.78 90.97 94.13 92.53 93.87 92.25 93.64 94.36 93.24 94.60 91.87 92.60 92.62 92.88 92.04 93.77 92.45
703 372 48 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 84.09 92.98 95.00 94.78 95.50 93.43 92.66 94.77 95.27 95.54 91.43 93.79 95.04 95.76 93.30 94.55 94.31 93.95 94.17 92.45 94.22 92.93 91.40 92.50 93.92
752 372 48 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 93.04 94.42 92.46 93.47 94.87 92.88 95.95 94.89 93.60 95.81 91.03 91.15 93.73 95.20 93.21 92.95 94.20 92.49 93.16 93.14 93.31 93.01 92.87 91.92 94.39
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 93.61 93.12 93.13 95.64 93.73 91.31 94.14 95.06 94.70 93.61 89.13 91.30 93.40 94.24 92.62 94.37 95.32 95.06 93.07 92.33 90.94 91.57 93.51 92.57 92.10
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 93.26 95.77 95.11 93.91 92.49 93.08 93.46 94.50 94.72 95.38 92.83 93.57 94.14 94.25 91.96 95.01 94.00 94.14 93.37 91.59 92.53 93.08 92.76 93.28 92.89
767 372 48 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 93.31 94.24 94.10 94.49 95.42 88.84 94.41 95.14 92.84 94.14 92.55 93.47 91.92 93.14 94.39 95.88 94.66 94.02 93.35 93.09 94.02 92.50 92.19 93.19 92.14
816 372 48 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 93.68 92.46 94.48 91.29 94.69 90.99 92.91 94.12 93.03 92.57 91.04 79.73 91.10 93.28 91.59 93.58 94.32 90.48 91.86 88.52 94.10 91.86 92.19 91.94 91.57
819 372 48 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 90.98 92.18 91.20 94.71 94.92 90.16 91.70 94.12 92.75 93.69 90.72 94.85 92.31 94.52 92.10 94.30 93.68 95.44 89.61 92.20 93.16 91.58 93.79 92.56 89.25
828 372 48 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 94.34 94.73 94.60 93.13 94.63 92.93 93.91 95.32 95.14 95.57 92.46 91.28 92.41 93.72 93.94 94.94 93.50 92.56 92.98 91.51 93.08 92.99 93.38 92.28 92.84
831 372 48 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 94.08 94.99 95.21 95.90 95.36 92.22 92.31 93.23 94.90 94.55 91.00 92.95 94.25 93.76 92.74 94.58 94.80 94.86 92.73 92.36 93.63 95.76 94.34 92.95 93.90
880 372 48 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 92.40 92.87 92.94 93.26 93.87 91.27 92.12 92.96 92.15 94.46 91.88 92.58 94.24 93.19 92.86 92.07 92.54 92.91 94.31 90.11 92.69 90.63 92.52 91.51 90.71
883 372 48 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 95.11 48.12 93.09 92.39 94.22 92.91 92.95 92.19 91.92 94.78 92.61 93.52 94.75 95.46 94.73 95.69 94.58 93.89 90.92 89.78 93.04 48.12 93.12 91.87 92.18
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 93.34 91.69 92.76 95.43 94.73 93.48 92.11 89.66 92.88 94.73 90.15 90.52 91.22 94.28 94.79 93.85 94.33 91.94 92.14 91.84 90.14 93.08 92.70 92.15 93.39
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 94.16 95.02 92.13 91.97 94.28 92.94 92.81 93.17 94.60 92.61 90.26 91.75 91.50 93.80 92.38 92.85 94.41 93.53 92.08 93.42 90.67 93.61 92.82 91.86 91.81
944 372 48 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 94.75 94.02 93.38 95.63 95.22 94.28 94.91 94.80 95.06 94.58 92.54 93.23 94.19 95.02 91.99 94.44 95.10 92.67 91.99 90.35 93.50 94.93 93.42 92.32 93.28
947 372 48 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 93.92 93.92 94.02 93.23 93.09 93.38 92.60 92.54 91.06 93.19 91.61 93.58 93.99 94.58 95.14 93.54 95.46 93.42 92.59 92.70 81.10 91.48 92.97 93.00 93.73
956 372 48 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 93.70 93.56 92.03 94.89 93.04 91.31 93.31 91.71 94.03 92.18 91.26 92.40 93.41 94.68 92.92 94.27 96.04 92.30 94.01 92.87 91.64 95.19 92.57 92.07 93.06
959 372 48 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 93.13 95.89 95.50 95.80 94.37 93.62 96.40 94.32 94.55 95.30 93.44 93.04 95.66 95.37 93.27 95.37 95.69 92.68 94.15 93.37 93.35 93.55 92.48 93.19 92.79
1008 372 48 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 94.31 93.71 93.93 96.45 94.52 92.26 93.23 95.15 92.52 94.69 91.66 91.12 94.70 94.74 93.41 94.92 94.55 95.26 92.97 94.03 93.13 94.56 93.77 93.00 93.84
1011 372 48 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 92.23 96.09 94.18 95.64 95.02 91.35 94.19 95.55 92.97 94.16 93.75 93.76 92.65 96.09 95.99 94.99 95.53 93.95 93.49 92.50 93.60 93.61 93.84 93.25 93.86
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 92.41 95.67 93.92 94.52 93.21 92.80 95.35 92.28 92.95 95.16 91.69 91.60 92.16 93.56 93.44 93.44 93.55 93.04 93.45 92.31 90.62 92.69 93.94 92.55 92.10
1023 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 93.28 94.55 93.49 95.79 93.38 83.27 93.95 95.16 94.72 94.29 93.58 93.91 93.90 94.54 90.75 93.75 94.37 93.53 92.04 91.84 93.15 92.52 91.91 93.12 93.14
1072 372 48 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 92.52 94.85 94.43 95.55 94.73 91.69 91.07 91.07 93.06 92.99 92.47 94.02 94.79 94.47 93.53 94.48 92.80 93.95 92.43 92.97 93.26 94.93 92.54 92.34 93.20
1075 372 48 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.49 94.85 94.50 93.13 96.27 91.99 93.29 93.16 93.00 95.93 92.93 93.14 93.46 94.45 93.91 91.38 94.13 95.89 94.46 91.76 92.34 92.75 91.14 93.50 91.41
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 93.87 92.20 93.45 94.87 94.46 92.63 91.70 92.63 94.57 95.12 91.70 91.67 94.30 94.98 92.07 95.26 96.38 92.74 92.54 91.48 92.70 93.12 91.53 92.21 93.46
1087 372 48 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 92.81 93.84 93.97 95.14 94.76 92.38 94.54 93.54 92.96 93.53 92.13 90.93 94.65 93.55 94.25 96.49 94.67 93.85 92.96 93.50 93.34 92.66 93.76 92.70 91.09
1136 372 48 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 96.20 93.42 91.44 91.88 94.63 92.54 93.83 91.64 95.43 92.78 92.58 93.22 94.44 95.07 94.48 92.29 94.10 93.11 93.07 92.96 91.18 93.11 91.52 91.09 91.33
1139 372 48 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 94.38 94.97 94.38 95.28 94.40 93.33 93.33 92.46 95.31 94.36 93.53 93.02 95.01 93.02 94.24 94.17 94.55 94.15 91.36 92.03 93.28 92.03 93.56 93.56 93.21
1148 372 48 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 93.38 95.56 92.77 92.17 94.11 92.53 93.89 93.87 93.22 93.75 93.19 93.41 94.15 94.64 92.42 92.56 92.20 94.57 92.05 94.51 91.49 94.60 91.87 89.41 93.36
1151 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 93.24 93.56 96.29 93.81 95.42 93.19 94.56 94.74 93.71 93.80 93.11 90.28 96.01 94.81 93.84 95.88 93.81 94.27 91.99 92.35 90.87 92.99 94.25 92.70 92.39
1200 372 48 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 93.16 92.05 92.75 90.22 92.08 92.44 91.48 95.44 91.73 92.29 88.80 90.51 92.00 93.00 94.02 92.83 92.84 90.00 90.75 90.18 92.88 91.39 92.31 91.78 91.83
1203 372 48 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 93.31 92.17 94.49 92.90 94.06 92.09 93.22 95.45 93.16 93.93 92.26 91.66 92.96 94.72 94.59 96.19 95.72 94.25 93.40 93.82 93.84 92.22 94.24 92.70 93.04
1212 372 48 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 92.68 93.71 93.03 93.52 94.51 92.76 94.51 92.39 94.12 95.03 93.60 92.59 94.09 96.34 90.96 92.87 92.25 95.81 92.20 90.62 92.29 94.49 92.91 92.11 92.63
1215 372 48 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 90.55 93.53 91.85 94.61 91.20 93.56 92.61 92.74 92.38 94.08 91.30 91.18 94.76 92.23 93.87 93.64 92.83 94.06 92.44 91.93 93.91 92.39 91.95 91.66 92.12
1264 372 48 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 91.43 92.57 93.60 92.88 93.57 93.07 92.33 92.56 93.26 95.39 94.09 90.26 94.98 94.53 92.91 94.09 93.06 93.23 91.81 89.70 92.44 90.72 92.77 91.06 89.37
1267 372 48 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 91.31 93.56 92.30 94.22 93.01 92.53 93.71 93.79 92.55 91.60 93.75 93.30 94.16 91.59 94.39 93.54 94.39 94.64 92.24 94.79 93.30 91.69 92.14 91.88 88.99
1276 372 48 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 93.66 92.50 93.88 93.63 92.56 94.59 94.42 92.46 93.22 94.52 92.42 92.43 93.17 94.56 93.38 94.50 96.05 94.91 93.22 93.98 91.43 92.14 93.71 92.22 91.17
1279 372 48 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 93.25 92.45 92.40 92.21 92.35 92.29 93.20 91.06 93.28 94.04 93.58 92.67 94.03 93.25 94.18 92.55 94.61 94.04 93.78 90.22 91.45 90.68 91.54 92.19 90.42
1328 372 48 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 93.19 95.10 94.26 89.79 93.22 94.08 90.66 92.42 94.06 94.68 93.32 91.78 94.59 96.77 92.83 92.76 95.03 95.58 93.15 91.98 91.20 93.87 94.27 92.05 91.46
1331 372 48 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 95.17 92.94 95.61 94.74 94.98 91.82 91.93 94.23 92.18 94.23 92.73 94.38 95.59 93.57 94.68 96.40 94.26 94.69 94.28 92.40 92.01 92.63 93.51 92.84 93.73
1340 372 48 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.28 94.38 94.37 94.62 93.37 92.37 94.79 92.56 94.39 94.78 93.40 94.49 93.88 95.06 92.24 95.56 94.73 93.54 94.35 93.91 92.21 91.85 94.38 93.24 92.63
1343 372 48 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.64 93.92 95.60 94.77 94.93 91.30 91.39 93.10 91.69 93.40 93.75 93.81 94.20 95.65 93.78 92.69 94.02 93.53 92.55 94.41 94.89 93.84 91.85 92.55 93.54
1392 372 48 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 93.02 91.84 94.23 91.08 93.50 91.87 93.00 95.09 93.32 92.71 93.26 91.45 93.54 94.65 93.74 93.77 93.70 92.59 90.84 90.68 93.60 92.80 94.01 92.24 92.24
1395 372 48 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 94.31 94.29 95.22 96.07 95.29 92.95 93.16 95.27 92.93 95.93 93.50 85.47 94.60 95.32 95.88 94.71 96.42 95.55 92.83 92.48 93.21 95.33 93.25 94.08 91.63
1404 372 48 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 92.11 93.81 91.61 91.39 93.60 92.08 92.92 93.10 92.90 94.32 92.47 92.85 91.45 92.41 95.02 92.21 93.33 92.12 91.70 92.73 92.84 93.24 93.05 94.65 93.78
1407 372 48 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 91.38 94.04 94.88 95.96 94.28 91.68 93.86 90.60 95.12 93.92 93.05 93.35 95.41 93.75 91.32 94.23 92.65 92.84 94.00 91.96 91.79 90.35 93.01 94.60 92.87
1456 372 48 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 91.01 93.96 95.24 94.94 93.53 91.72 93.17 88.14 95.35 91.72 93.18 91.08 94.08 93.03 91.15 94.53 93.54 93.74 91.88 90.53 92.68 92.52 92.74 93.35 93.24
1459 372 48 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 94.46 94.62 93.29 93.30 92.62 92.66 91.63 93.41 92.13 94.27 91.57 92.20 93.96 93.82 91.34 95.55 95.11 92.01 93.01 91.86 92.76 92.68 93.27 92.89 91.48
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 95.45 93.46 94.52 94.43 93.34 91.22 94.70 95.07 93.99 94.76 93.87 93.91 93.78 94.33 93.36 93.07 95.14 93.55 91.42 91.41 92.88 93.94 93.48 91.78 93.81
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 93.04 94.32 95.51 91.97 95.26 92.57 94.78 93.55 93.33 95.08 92.89 91.94 91.30 95.10 92.88 94.06 93.07 94.96 93.84 90.36 93.06 94.26 92.97 92.60 91.87
1520 372 48 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 92.30 93.84 94.66 94.50 93.95 93.04 93.67 94.71 96.05 95.08 92.39 91.27 94.97 93.90 93.44 95.05 95.08 94.64 93.38 93.19 93.58 93.82 92.51 92.89 92.31
1523 372 48 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 94.25 94.80 95.10 95.30 95.90 93.08 95.21 93.49 95.06 95.90 93.02 92.22 95.28 95.56 94.87 95.62 94.41 93.68 91.70 93.52 92.77 91.96 92.99 91.74 93.52
1532 372 48 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 94.30 93.21 93.59 95.49 95.07 92.96 94.00 93.49 92.71 94.31 94.79 93.65 94.28 93.78 94.97 93.66 96.08 93.93 93.12 91.86 92.67 93.19 93.61 93.67 91.59
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 94.87 94.80 94.27 95.36 94.47 93.55 92.80 95.32 93.43 93.66 93.12 92.23 93.32 92.50 94.79 95.24 93.06 93.55 94.58 92.18 94.48 92.58 93.41 91.74 93.62
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 85.60 87.07 86.35 90.41 85.34 87.96 85.23 87.80 86.79 89.02 88.58 87.93 86.76 85.46 86.77 87.08 87.41 87.66 88.73 89.30 89.08 89.63 88.91 89.66 89.09
1023 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 84.33 86.79 87.50 88.68 85.99 90.55 88.03 86.45 87.50 88.57 87.07 89.91 87.59 87.17 86.97 88.85 88.96 86.76 88.03 87.13 89.36 88.05 90.22 87.84 87.12
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.31 87.36 87.02 85.20 88.81 86.82 87.76 85.98 88.76 88.09 91.31 88.19 88.26 85.73 87.49 88.29 86.44 88.29 90.18 87.33 90.03 89.41 89.05 87.39 88.70
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 87.90 86.66 86.71 85.40 87.97 89.21 86.53 84.85 88.66 86.64 88.41 87.14 87.23 87.33 87.33 88.78 88.90 86.67 91.27 87.59 89.03 88.67 89.27 88.59 89.84
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.25 86.75 87.45 90.66 84.77 86.47 88.10 86.77 84.65 86.68 88.72 89.57 89.73 83.16 86.04 88.15 85.51 89.01 88.81 91.07 89.49 89.02 90.18 88.63 87.06
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 87.37 86.62 87.45 86.35 88.49 89.31 86.41 90.66 87.17 85.77 89.63 88.47 87.05 88.37 87.99 87.58 86.36 86.24 90.28 89.40 88.24 93.05 89.50 90.33 89.35
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 87.05 87.43 87.24 85.47 86.21 88.10 86.70 88.84 88.14 87.37 89.02 87.30 88.20 86.63 86.45 88.11 86.91 86.36 88.77 89.88 88.52 88.89 89.66 88.68 89.26
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 85.61 88.38 85.63 87.49 87.86 87.52 85.12 86.15 86.89 87.75 88.74 87.45 89.02 87.14 87.37 88.88 86.57 87.43 88.44 89.52 89.36 89.52 89.02 90.31 88.79
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 88.63 88.33 87.15 86.58 89.23 88.69 88.24 87.40 89.00 86.43 87.32 89.68 87.52 88.24 88.39 89.32 85.88 87.85 88.06 89.80 89.57 88.35 87.96 89.94 90.95
127 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.52 85.82 86.31 86.99 87.74 87.99 86.04 86.08 88.75 87.09 87.63 90.45 88.72 87.64 90.28 87.88 87.44 86.95 88.64 88.30 88.01 89.05 88.02 88.49 88.94
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 87.32 88.00 86.61 86.65 86.67 89.92 88.18 87.08 89.73 86.18 87.98 89.14 87.43 87.64 87.01 89.51 86.58 88.45 89.12 89.51 89.09 87.84 88.45 89.98 86.23
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 87.97 87.43 86.48 86.58 87.77 86.80 85.76 85.76 87.22 88.65 87.76 87.33 88.35 87.87 87.71 86.89 86.82 87.85 92.34 89.92 89.74 89.21 89.32 91.17 91.82
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 86.55 86.72 86.63 87.15 86.06 88.33 89.32 86.37 88.37 86.80 89.27 88.61 87.47 87.79 86.53 85.97 87.84 85.55 88.32 89.40 88.20 90.20 88.40 89.82 88.98
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 88.36 86.85 87.99 87.14 86.38 87.14 87.33 86.59 86.02 86.24 90.63 89.15 89.56 86.25 86.79 87.56 85.76 86.38 88.67 89.39 89.22 88.00 87.90 88.63 90.68
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 85.43 87.50 89.00 86.80 86.12 86.31 86.95 85.54 86.01 86.10 87.92 88.16 87.81 87.67 86.52 87.75 90.14 87.07 89.75 92.23 88.93 88.88 88.37 88.85 88.22
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.15 89.30 86.12 86.29 88.10 87.95 87.62 89.40 88.18 85.85 89.19 89.72 89.27 87.64 85.49 85.87 87.27 87.85 89.46 89.46 90.70 89.08 87.53 89.91 90.16
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.51 88.86 86.31 85.30 87.49 88.14 87.27 88.62 87.45 88.43 88.58 87.60 87.37 83.51 84.52 89.82 85.67 87.12 88.59 90.26 89.54 88.72 90.84 88.24 88.59
Size of the All data:  (96, 28)
Size of the Sig data:  (17, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
14 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 92.41 95.67 93.92 94.52 93.21 92.80 95.35 92.28 92.95 95.16 91.69 91.60 92.16 93.56 93.44 93.44 93.55 93.04 93.45 92.31 90.62 92.69 93.94 92.55 92.10
8 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 93.28 94.55 93.49 95.79 93.38 83.27 93.95 95.16 94.72 94.29 93.58 93.91 93.90 94.54 90.75 93.75 94.37 93.53 92.04 91.84 93.15 92.52 91.91 93.12 93.14
5 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 93.23 95.25 92.71 93.39 93.96 91.78 92.47 93.87 94.74 94.94 91.90 94.74 93.30 92.93 94.05 95.55 94.67 93.63 92.65 89.88 94.25 92.06 92.78 91.43 93.27
6 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 95.45 93.46 94.52 94.43 93.34 91.22 94.70 95.07 93.99 94.76 93.87 93.91 93.78 94.33 93.36 93.07 95.14 93.55 91.42 91.41 92.88 93.94 93.48 91.78 93.81
15 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 93.04 94.32 95.51 91.97 95.26 92.57 94.78 93.55 93.33 95.08 92.89 91.94 91.30 95.10 92.88 94.06 93.07 94.96 93.84 90.36 93.06 94.26 92.97 92.60 91.87
1 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.56 93.20 95.32 93.18 93.09 91.37 94.42 93.38 94.33 90.86 93.95 90.55 92.68 93.35 93.55 93.65 96.17 92.59 91.94 93.39 91.20 91.64 92.62 91.37 93.61
9 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 93.34 91.69 92.76 95.43 94.73 93.48 92.11 89.66 92.88 94.73 90.15 90.52 91.22 94.28 94.79 93.85 94.33 91.94 92.14 91.84 90.14 93.08 92.70 92.15 93.39
7 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 94.16 95.02 92.13 91.97 94.28 92.94 92.81 93.17 94.60 92.61 90.26 91.75 91.50 93.80 92.38 92.85 94.41 93.53 92.08 93.42 90.67 93.61 92.82 91.86 91.81
0 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 93.87 92.20 93.45 94.87 94.46 92.63 91.70 92.63 94.57 95.12 91.70 91.67 94.30 94.98 92.07 95.26 96.38 92.74 92.54 91.48 92.70 93.12 91.53 92.21 93.46
13 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.52 92.37 94.59 93.73 95.07 92.57 93.22 92.69 95.96 93.10 94.14 90.79 94.15 96.09 89.53 93.70 94.96 93.76 94.41 92.78 92.75 92.36 89.65 91.54 89.07
4 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 93.71 94.56 90.96 94.57 92.55 89.98 95.28 94.57 94.32 93.75 93.04 90.96 95.36 93.09 92.27 91.81 95.07 94.65 90.15 92.35 93.34 91.22 93.76 91.11 91.68
3 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 93.60 95.85 93.82 95.20 93.83 91.42 96.37 93.65 94.94 93.29 92.14 94.10 92.97 94.34 92.59 93.16 95.08 92.05 92.36 91.99 93.15 92.27 92.37 93.10 92.66
10 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 93.95 91.41 90.78 95.00 94.22 91.58 94.07 94.24 93.00 93.35 92.59 93.98 94.57 94.77 94.41 95.55 91.64 91.90 92.53 93.35 93.70 93.71 92.50 92.18 91.75
11 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 94.21 94.96 92.77 94.52 93.78 92.43 94.31 94.22 95.81 94.24 91.99 93.11 92.54 94.26 94.06 92.77 96.25 94.59 92.83 92.40 93.52 93.36 93.92 94.77 92.14
12 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 94.87 94.80 94.27 95.36 94.47 93.55 92.80 95.32 93.43 93.66 93.12 92.23 93.32 92.50 94.79 95.24 93.06 93.55 94.58 92.18 94.48 92.58 93.41 91.74 93.62
2 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 93.61 93.12 93.13 95.64 93.73 91.31 94.14 95.06 94.70 93.61 89.13 91.30 93.40 94.24 92.62 94.37 95.32 95.06 93.07 92.33 90.94 91.57 93.51 92.57 92.10
16 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 93.94 92.61 92.99 91.60 93.62 92.79 94.98 94.40 93.57 94.08 91.30 89.75 94.38 91.24 94.74 93.57 95.51 94.78 93.46 89.55 93.61 91.50 94.72 92.09 88.73
Size of the test data:  (17, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.43 3.75 6.68 6.30 6.13 4.65 7.71 5.78 6.12 5.65 2.72 2.15 7.01 7.73 10.22 3.75 9.84 7.66 4.87 -0.71 4.07 2.78 3.88 3.85 0.14 1
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.46 3.82 7.01 9.35 5.63 3.36 6.52 5.66 6.52 7.76 -0.06 1.58 4.13 6.60 7.13 8.50 8.05 7.21 3.61 2.87 0.24 2.49 5.98 2.66 1.94 1
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.44 7.30 5.27 8.56 8.35 7.24 5.85 9.78 7.42 7.56 5.20 4.07 5.51 4.83 8.27 7.49 2.92 6.48 4.83 -0.05 5.55 3.70 5.04 2.89 5.40 1
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.79 7.57 8.06 1.31 10.49 6.10 6.68 6.78 8.68 8.40 4.17 2.37 1.57 11.94 6.84 5.91 7.56 5.95 5.03 -0.71 3.57 5.24 2.79 3.97 4.81 1
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.19 6.58 7.87 6.83 4.60 2.06 8.01 2.72 7.16 5.09 4.32 2.08 5.63 4.98 5.56 6.07 9.81 6.35 1.66 3.99 2.96 -1.41 3.12 1.04 4.26 1
1023 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.95 7.76 5.99 7.11 7.39 -7.28 5.92 8.71 7.22 5.72 6.51 4.00 6.31 7.37 3.78 4.90 5.41 6.77 4.01 4.71 3.79 4.47 1.69 5.28 6.02 1
127 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.00 6.55 8.28 6.74 7.33 4.58 7.18 6.61 7.21 6.01 6.51 0.34 5.43 8.45 -0.75 5.82 7.52 6.81 5.77 4.48 4.74 3.31 1.63 3.05 0.13 1
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.63 8.42 7.34 8.62 6.06 4.62 10.61 7.89 7.72 4.64 4.38 6.77 4.62 6.47 4.88 6.27 8.26 4.20 0.02 2.07 3.41 3.06 3.05 1.93 0.84 0
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.85 8.11 4.78 7.38 7.40 5.29 6.98 7.63 9.79 8.00 1.36 3.96 2.98 8.01 7.27 5.21 10.49 8.21 4.16 3.01 4.30 5.36 6.02 6.14 1.46 0
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.40 4.69 4.15 7.85 8.16 3.25 4.75 7.87 4.63 6.55 3.32 5.37 7.10 6.98 7.88 9.58 3.80 6.35 4.21 3.95 5.50 3.51 4.10 2.36 2.77 0
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.81 8.60 7.57 4.11 7.87 4.84 10.12 4.48 6.16 6.14 3.11 3.67 5.40 8.10 6.67 6.36 6.14 5.38 4.72 3.01 1.54 3.06 5.03 2.89 3.01 0
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.39 6.56 4.35 7.92 5.88 0.06 7.10 7.49 4.59 7.57 5.06 1.82 7.93 5.45 5.26 2.30 8.49 6.20 1.03 2.84 4.25 3.38 5.31 1.13 5.45 0
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.55 6.64 6.50 4.48 6.42 5.42 7.69 7.02 7.71 4.86 1.52 4.30 2.48 6.66 5.01 3.97 7.84 6.10 3.64 3.90 1.31 4.09 3.80 1.55 3.02 0
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.29 4.26 5.52 9.96 8.52 5.38 5.41 0.82 4.74 7.36 1.13 3.22 3.02 7.65 8.34 5.74 7.42 5.58 3.37 1.96 1.62 4.19 3.04 3.47 4.13 0
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.55 6.80 7.81 9.03 5.37 2.01 8.17 10.22 5.33 8.12 5.46 6.77 6.55 7.00 6.03 4.29 6.24 6.88 0.15 3.82 3.85 5.27 4.21 3.19 3.97 0
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.92 7.89 5.69 8.19 5.15 4.96 4.71 7.89 5.98 6.85 0.59 6.55 5.04 7.20 6.56 7.26 8.23 5.34 2.47 2.55 4.22 2.65 3.73 4.04 4.57 0
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.24 3.87 6.30 8.29 5.23 3.94 3.46 5.23 5.57 8.69 4.38 1.99 6.78 6.74 3.68 5.94 10.50 4.89 4.48 1.68 3.13 4.77 3.57 2.27 2.51 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_20 89.381765 1.278589
mAP_valid_abs_values_19 89.262353 1.175976
mAP_valid_abs_values_25 89.203529 1.018945
mAP_valid_abs_values_21 89.182941 0.686575
mAP_valid_abs_values_22 89.151176 1.178643
mAP_valid_abs_values_26 89.045882 1.429082
mAP_valid_abs_values_23 88.976471 0.921995
mAP_valid_abs_values_11 88.691765 1.115226
mAP_valid_abs_values_12 88.576471 1.050880
mAP_valid_abs_values_13 88.078824 0.908053
mAP_valid_abs_values_6 88.071176 1.196379
mAP_valid_abs_values_16 88.017059 1.138452
mAP_valid_abs_values_9 87.605294 1.293204
mAP_valid_abs_values_2 87.404118 0.910385
mAP_valid_abs_values_18 87.264118 0.903853
mAP_valid_abs_values_10 87.156471 1.069006
mAP_valid_abs_values_5 87.117647 1.275463
mAP_valid_abs_values_7 87.093529 1.155595
mAP_valid_abs_values_17 87.085882 1.280430
mAP_valid_abs_values_8 87.078824 1.534759
mAP_valid_abs_values_15 87.038235 1.245985
mAP_valid_abs_values_4 87.008235 1.592954
mAP_valid_abs_values_3 86.938235 0.803129
mAP_valid_abs_values_14 86.778824 1.529064
mAP_valid_abs_values 86.462353 1.393402


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_17 94.645882 1.257040
mAP_test_abs_values_9 94.225882 0.932128
mAP_test_abs_values_4 94.186471 1.336128
mAP_test_abs_values_7 93.968235 1.276872
mAP_test_abs_values_14 93.964706 1.127126
mAP_test_abs_values_5 93.940000 0.726051
mAP_test_abs_values_10 93.919412 1.108397
mAP_test_abs_values_16 93.861765 1.053086
mAP_test_abs_values_2 93.825882 1.417705
mAP_test_abs_values_8 93.701176 1.397130
mAP_test_abs_values 93.632353 0.802773
mAP_test_abs_values_18 93.520588 1.046174
mAP_test_abs_values_3 93.360000 1.321708
mAP_test_abs_values_13 93.225294 1.203854
average_map 93.211318 0.306089
mAP_test_abs_values_15 93.075294 1.444641
mAP_test_abs_values_23 92.858235 1.148843
mAP_test_abs_values_19 92.675882 1.091639
mAP_test_abs_values_22 92.675882 0.913572
mAP_test_abs_values_21 92.597647 1.351409
mAP_test_abs_values_26 92.247647 1.466226
mAP_test_abs_values_25 92.245294 0.868548
mAP_test_abs_values_11 92.202353 1.426278
mAP_test_abs_values_12 92.165294 1.514117
mAP_test_abs_values_20 91.932941 1.136858
mAP_test_abs_values_6 91.628824 2.344754
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 85.60 87.07 86.35 90.41 85.34 87.96 85.23 87.80 86.79 89.02 88.58 87.93 86.76 85.46 86.77 87.08 87.41 87.66 88.73 89.30 89.08 89.63 88.91 89.66 89.09
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.31 87.36 87.02 85.20 88.81 86.82 87.76 85.98 88.76 88.09 91.31 88.19 88.26 85.73 87.49 88.29 86.44 88.29 90.18 87.33 90.03 89.41 89.05 87.39 88.70
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 87.90 86.66 86.71 85.40 87.97 89.21 86.53 84.85 88.66 86.64 88.41 87.14 87.23 87.33 87.33 88.78 88.90 86.67 91.27 87.59 89.03 88.67 89.27 88.59 89.84
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.25 86.75 87.45 90.66 84.77 86.47 88.10 86.77 84.65 86.68 88.72 89.57 89.73 83.16 86.04 88.15 85.51 89.01 88.81 91.07 89.49 89.02 90.18 88.63 87.06
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 87.37 86.62 87.45 86.35 88.49 89.31 86.41 90.66 87.17 85.77 89.63 88.47 87.05 88.37 87.99 87.58 86.36 86.24 90.28 89.40 88.24 93.05 89.50 90.33 89.35
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 85.61 88.38 85.63 87.49 87.86 87.52 85.12 86.15 86.89 87.75 88.74 87.45 89.02 87.14 87.37 88.88 86.57 87.43 88.44 89.52 89.36 89.52 89.02 90.31 88.79
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 88.63 88.33 87.15 86.58 89.23 88.69 88.24 87.40 89.00 86.43 87.32 89.68 87.52 88.24 88.39 89.32 85.88 87.85 88.06 89.80 89.57 88.35 87.96 89.94 90.95
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 87.32 88.00 86.61 86.65 86.67 89.92 88.18 87.08 89.73 86.18 87.98 89.14 87.43 87.64 87.01 89.51 86.58 88.45 89.12 89.51 89.09 87.84 88.45 89.98 86.23
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 87.97 87.43 86.48 86.58 87.77 86.80 85.76 85.76 87.22 88.65 87.76 87.33 88.35 87.87 87.71 86.89 86.82 87.85 92.34 89.92 89.74 89.21 89.32 91.17 91.82
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 86.55 86.72 86.63 87.15 86.06 88.33 89.32 86.37 88.37 86.80 89.27 88.61 87.47 87.79 86.53 85.97 87.84 85.55 88.32 89.40 88.20 90.20 88.40 89.82 88.98
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.15 89.30 86.12 86.29 88.10 87.95 87.62 89.40 88.18 85.85 89.19 89.72 89.27 87.64 85.49 85.87 87.27 87.85 89.46 89.46 90.70 89.08 87.53 89.91 90.16
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.51 88.86 86.31 85.30 87.49 88.14 87.27 88.62 87.45 88.43 88.58 87.60 87.37 83.51 84.52 89.82 85.67 87.12 88.59 90.26 89.54 88.72 90.84 88.24 88.59
Size of the All data:  (96, 28)
Size of the Sig data:  (12, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
9 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 92.41 95.67 93.92 94.52 93.21 92.80 95.35 92.28 92.95 95.16 91.69 91.60 92.16 93.56 93.44 93.44 93.55 93.04 93.45 92.31 90.62 92.69 93.94 92.55 92.10
5 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 93.23 95.25 92.71 93.39 93.96 91.78 92.47 93.87 94.74 94.94 91.90 94.74 93.30 92.93 94.05 95.55 94.67 93.63 92.65 89.88 94.25 92.06 92.78 91.43 93.27
6 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 95.45 93.46 94.52 94.43 93.34 91.22 94.70 95.07 93.99 94.76 93.87 93.91 93.78 94.33 93.36 93.07 95.14 93.55 91.42 91.41 92.88 93.94 93.48 91.78 93.81
10 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 93.04 94.32 95.51 91.97 95.26 92.57 94.78 93.55 93.33 95.08 92.89 91.94 91.30 95.10 92.88 94.06 93.07 94.96 93.84 90.36 93.06 94.26 92.97 92.60 91.87
1 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.56 93.20 95.32 93.18 93.09 91.37 94.42 93.38 94.33 90.86 93.95 90.55 92.68 93.35 93.55 93.65 96.17 92.59 91.94 93.39 91.20 91.64 92.62 91.37 93.61
7 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 94.16 95.02 92.13 91.97 94.28 92.94 92.81 93.17 94.60 92.61 90.26 91.75 91.50 93.80 92.38 92.85 94.41 93.53 92.08 93.42 90.67 93.61 92.82 91.86 91.81
0 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 93.87 92.20 93.45 94.87 94.46 92.63 91.70 92.63 94.57 95.12 91.70 91.67 94.30 94.98 92.07 95.26 96.38 92.74 92.54 91.48 92.70 93.12 91.53 92.21 93.46
4 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 93.71 94.56 90.96 94.57 92.55 89.98 95.28 94.57 94.32 93.75 93.04 90.96 95.36 93.09 92.27 91.81 95.07 94.65 90.15 92.35 93.34 91.22 93.76 91.11 91.68
3 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 93.60 95.85 93.82 95.20 93.83 91.42 96.37 93.65 94.94 93.29 92.14 94.10 92.97 94.34 92.59 93.16 95.08 92.05 92.36 91.99 93.15 92.27 92.37 93.10 92.66
8 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 93.95 91.41 90.78 95.00 94.22 91.58 94.07 94.24 93.00 93.35 92.59 93.98 94.57 94.77 94.41 95.55 91.64 91.90 92.53 93.35 93.70 93.71 92.50 92.18 91.75
2 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 93.61 93.12 93.13 95.64 93.73 91.31 94.14 95.06 94.70 93.61 89.13 91.30 93.40 94.24 92.62 94.37 95.32 95.06 93.07 92.33 90.94 91.57 93.51 92.57 92.10
11 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 93.94 92.61 92.99 91.60 93.62 92.79 94.98 94.40 93.57 94.08 91.30 89.75 94.38 91.24 94.74 93.57 95.51 94.78 93.46 89.55 93.61 91.50 94.72 92.09 88.73
Size of the test data:  (12, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

key_values = ['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']
print('Are the keys of the valid and test dfs same?: ',dt_mw[key_values].equals(test_data_mw1[key_values]))
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.79 7.57 8.06 1.31 10.49 6.10 6.68 6.78 8.68 8.40 4.17 2.37 1.57 11.94 6.84 5.91 7.56 5.95 5.03 -0.71 3.57 5.24 2.79 3.97 4.81 1
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.19 6.58 7.87 6.83 4.60 2.06 8.01 2.72 7.16 5.09 4.32 2.08 5.63 4.98 5.56 6.07 9.81 6.35 1.66 3.99 2.96 -1.41 3.12 1.04 4.26 1
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.46 3.82 7.01 9.35 5.63 3.36 6.52 5.66 6.52 7.76 -0.06 1.58 4.13 6.60 7.13 8.50 8.05 7.21 3.61 2.87 0.24 2.49 5.98 2.66 1.94 1
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.43 3.75 6.68 6.30 6.13 4.65 7.71 5.78 6.12 5.65 2.72 2.15 7.01 7.73 10.22 3.75 9.84 7.66 4.87 -0.71 4.07 2.78 3.88 3.85 0.14 1
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.81 8.60 7.57 4.11 7.87 4.84 10.12 4.48 6.16 6.14 3.11 3.67 5.40 8.10 6.67 6.36 6.14 5.38 4.72 3.01 1.54 3.06 5.03 2.89 3.01 0
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.92 7.89 5.69 8.19 5.15 4.96 4.71 7.89 5.98 6.85 0.59 6.55 5.04 7.20 6.56 7.26 8.23 5.34 2.47 2.55 4.22 2.65 3.73 4.04 4.57 0
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.55 6.80 7.81 9.03 5.37 2.01 8.17 10.22 5.33 8.12 5.46 6.77 6.55 7.00 6.03 4.29 6.24 6.88 0.15 3.82 3.85 5.27 4.21 3.19 3.97 0
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.55 6.64 6.50 4.48 6.42 5.42 7.69 7.02 7.71 4.86 1.52 4.30 2.48 6.66 5.01 3.97 7.84 6.10 3.64 3.90 1.31 4.09 3.80 1.55 3.02 0
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.24 3.87 6.30 8.29 5.23 3.94 3.46 5.23 5.57 8.69 4.38 1.99 6.78 6.74 3.68 5.94 10.50 4.89 4.48 1.68 3.13 4.77 3.57 2.27 2.51 0
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.39 6.56 4.35 7.92 5.88 0.06 7.10 7.49 4.59 7.57 5.06 1.82 7.93 5.45 5.26 2.30 8.49 6.20 1.03 2.84 4.25 3.38 5.31 1.13 5.45 0
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.63 8.42 7.34 8.62 6.06 4.62 10.61 7.89 7.72 4.64 4.38 6.77 4.62 6.47 4.88 6.27 8.26 4.20 0.02 2.07 3.41 3.06 3.05 1.93 0.84 0
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.40 4.69 4.15 7.85 8.16 3.25 4.75 7.87 4.63 6.55 3.32 5.37 7.10 6.98 7.88 9.58 3.80 6.35 4.21 3.95 5.50 3.51 4.10 2.36 2.77 0
Are the keys of the valid and test dfs same?:  False

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_25 89.497500 1.065092
mAP_valid_abs_values_19 89.466667 1.310401
mAP_valid_abs_values_22 89.391667 1.308829
mAP_valid_abs_values_20 89.380000 1.024926
mAP_valid_abs_values_21 89.339167 0.696569
mAP_valid_abs_values_26 89.130000 1.521751
mAP_valid_abs_values_23 89.035833 0.909740
mAP_valid_abs_values_11 88.790833 1.025329
mAP_valid_abs_values_12 88.402500 0.948023
mAP_valid_abs_values_6 88.093333 1.077643
mAP_valid_abs_values_16 88.011667 1.339449
mAP_valid_abs_values_13 87.955000 0.957179
mAP_valid_abs_values_9 87.739167 1.344264
mAP_valid_abs_values_2 87.623333 0.928374
mAP_valid_abs_values_18 87.497500 0.973654
mAP_valid_abs_values_5 87.380000 1.387634
mAP_valid_abs_values_8 87.236667 1.659328
mAP_valid_abs_values_10 87.190833 1.138823
mAP_valid_abs_values_7 87.128333 1.318869
mAP_valid_abs_values_4 87.005000 1.793369
mAP_valid_abs_values_15 86.886667 1.102644
mAP_valid_abs_values_17 86.770833 0.967033
mAP_valid_abs_values 86.680833 1.249017
mAP_valid_abs_values_3 86.659167 0.541655
mAP_valid_abs_values_14 86.656667 1.789842


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_4 94.296667 1.122720
mAP_test_abs_values_17 94.182083 1.310986
mAP_test_abs_values_14 94.123958 0.930954
mAP_test_abs_values_5 93.846458 1.119767
mAP_test_abs_values_7 93.823750 1.397590
mAP_test_abs_values_13 93.802708 1.143032
mAP_test_abs_values_9 93.777917 1.039709
mAP_test_abs_values_16 93.701458 2.056142
mAP_test_abs_values_8 93.668542 1.776147
mAP_test_abs_values_18 93.499167 1.297836
mAP_test_abs_values 93.317083 1.754463
mAP_test_abs_values_15 93.155833 1.374008
mAP_test_abs_values_10 93.058542 6.741124
average_map 92.970192 0.896944
mAP_test_abs_values_23 92.909375 0.799450
mAP_test_abs_values_2 92.876250 6.748060
mAP_test_abs_values_21 92.700625 1.225030
mAP_test_abs_values_3 92.630208 6.714049
mAP_test_abs_values_12 92.420208 1.383664
mAP_test_abs_values_11 92.382292 1.258762
mAP_test_abs_values_26 92.251667 1.211190
mAP_test_abs_values_22 91.933333 6.539201
mAP_test_abs_values_6 91.848750 1.680716
mAP_test_abs_values_19 91.531042 6.493397
mAP_test_abs_values_25 91.520417 6.435556
mAP_test_abs_values_20 90.996458 6.417313


Summary using radar plot

Code
def extract_number(text):
    if isinstance(text, str):
        matches = re.findall(r'\d+', text)
        return int(matches[0]) if matches else 1
    return 1

res_valid1['id'] = res_valid1.index.to_series().apply(extract_number)
res_test1['id'] = res_test1.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid1,res_test1])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test1 = res_test1.sort_values(by=['id']).reset_index().query("index !='average_map'")
data_range1 = np.array(list(res_test1['mean']) + list(res_valid1['mean']))
categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test1['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid1['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()

##############


res_valid2['id'] = res_valid2.index.to_series().apply(extract_number)
res_test2['id'] = res_test2.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid2,res_test2])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test2 = res_test2.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res_test2['mean']) + list(res_valid2['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test2['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid2['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()




  • In these experimental results, the thresholding is based on a fixed value of 0. This decision is informed by the fact that the binary-like hash values are symmetrically distributed between -1 and 1.
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
48 372 48 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 84.33 84.25 86.57 85.57 85.37 86.02 84.52 86.70 83.63 86.06 85.84 87.70 86.80 84.25 84.93 85.19 82.44 85.28 88.69 90.66 88.10 85.45 88.59 86.61 87.02
51 372 48 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 84.12 87.41 84.97 88.79 85.10 86.92 91.25 84.56 87.91 85.90 87.77 88.38 88.15 83.26 83.69 85.42 86.22 85.30 87.66 88.78 89.96 90.19 88.86 88.17 86.85
60 372 48 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 84.86 86.14 85.22 85.95 82.35 43.72 83.56 89.27 84.94 87.89 88.35 86.37 43.72 43.72 86.52 86.69 86.03 43.72 88.45 87.46 88.17 89.31 86.90 88.41 89.28
63 372 48 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 84.33 84.87 84.94 85.44 85.05 87.47 85.72 88.76 85.19 84.17 87.83 87.04 86.83 87.52 85.46 88.03 84.29 86.88 86.75 89.62 87.93 86.21 88.39 87.51 87.70
112 372 48 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 85.46 84.82 85.39 84.50 87.67 87.58 82.54 87.31 86.38 84.12 87.60 87.59 87.09 86.31 87.60 88.18 85.11 87.47 88.37 86.89 89.43 88.57 88.19 87.78 88.73
115 372 48 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 84.11 85.80 86.76 84.18 85.98 86.80 85.68 87.43 85.80 85.78 86.77 88.39 87.55 85.61 85.55 85.68 86.56 85.58 87.26 90.42 89.22 87.51 89.67 88.66 88.75
124 372 48 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 86.26 87.10 86.70 85.74 85.73 87.02 85.71 86.90 87.49 85.10 87.92 87.98 88.11 88.09 87.95 87.56 86.75 87.22 88.51 88.11 89.44 88.82 89.68 89.00 88.74
127 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.52 84.96 86.31 86.87 87.52 87.96 85.68 85.63 88.25 87.08 87.59 89.82 88.50 87.64 88.62 87.52 86.43 86.94 88.51 88.28 87.82 88.94 87.86 88.06 88.85
176 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 87.68 86.69 43.72 84.53 83.73 86.66 85.94 87.61 86.84 87.96 87.53 88.18 86.48 85.56 87.26 86.63 86.36 87.18 87.39 86.94 89.36 89.13 84.66 88.02 87.17
179 372 48 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 84.84 87.46 84.84 83.88 85.38 88.80 82.85 85.42 86.83 85.91 86.37 88.40 87.77 87.30 88.11 86.79 86.45 83.87 89.05 90.28 88.32 87.25 90.12 88.52 89.05
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.51 88.84 86.31 85.26 86.95 87.67 86.64 88.40 87.31 88.42 88.58 87.57 87.37 83.06 84.12 89.56 85.67 87.02 88.59 90.20 89.16 88.69 90.84 88.18 88.10
191 372 48 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.23 87.70 85.03 84.92 87.99 87.59 85.17 84.59 87.20 84.65 87.54 87.08 87.47 87.10 85.65 87.35 84.85 86.86 87.24 90.19 86.33 88.70 88.37 88.66 90.41
240 372 48 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 84.38 43.72 83.18 88.42 85.42 86.63 83.58 84.89 84.16 83.87 87.87 87.96 86.10 85.78 85.28 87.55 86.88 87.38 84.85 88.40 89.06 85.91 88.04 89.06 87.46
243 372 48 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 82.91 86.34 87.16 87.24 84.69 86.55 85.07 86.38 85.90 84.43 85.54 85.59 87.86 84.64 86.39 85.43 86.01 85.92 87.86 91.04 87.26 88.32 87.93 86.59 87.95
252 372 48 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 84.13 85.41 84.58 85.18 88.28 86.95 86.25 86.44 84.00 84.65 86.57 88.48 87.34 86.98 87.90 85.69 86.44 87.29 88.15 87.90 88.42 89.09 88.49 86.94 88.64
255 372 48 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 85.77 84.73 88.24 86.98 85.11 87.41 84.88 85.44 86.81 85.22 86.43 89.79 86.02 84.34 86.29 85.53 86.74 86.75 87.79 88.13 88.92 89.25 88.72 87.18 88.74
304 372 48 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 85.12 85.61 85.15 87.09 86.42 87.76 86.19 83.60 84.73 86.51 89.27 88.66 88.41 88.23 85.02 86.95 86.13 86.33 89.74 87.66 88.73 88.34 88.32 88.34 88.10
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 86.73 87.99 86.54 86.40 86.67 89.27 87.74 86.81 89.71 86.17 87.91 88.32 87.14 87.46 86.59 88.63 86.55 88.45 88.79 89.51 89.08 87.59 88.33 89.97 85.85
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 87.97 87.19 86.32 86.34 87.51 86.80 85.44 85.73 87.22 87.14 87.76 87.18 88.11 86.65 87.70 86.70 86.74 87.49 91.85 89.82 89.47 88.73 89.06 91.07 91.68
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 86.46 86.67 86.34 87.15 85.56 88.09 89.13 86.37 88.11 85.97 89.27 88.36 87.43 87.66 86.40 85.95 87.84 85.50 88.21 88.75 87.69 89.97 87.71 88.93 88.75
368 372 48 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 88.47 85.59 85.77 86.64 85.11 87.86 86.10 85.19 86.99 87.59 87.45 87.62 88.54 86.92 86.93 87.53 85.33 88.12 89.23 88.02 89.33 89.49 87.32 88.71 87.48
371 372 48 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 85.96 85.25 83.72 86.77 85.57 85.51 85.91 86.86 85.74 85.65 87.97 87.64 86.37 84.60 86.29 86.28 87.26 85.38 88.09 86.80 87.98 90.18 88.21 88.98 88.56
380 372 48 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 85.43 86.26 86.61 84.98 90.32 87.91 84.87 85.45 87.97 88.34 86.89 87.58 84.76 84.23 86.25 86.64 89.95 87.60 88.34 88.50 89.70 89.48 86.89 88.65 88.79
383 372 48 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 85.16 86.54 86.22 86.29 88.07 87.11 87.15 86.02 85.81 86.96 88.27 87.31 85.68 87.05 84.26 86.84 87.19 87.64 90.57 86.81 88.46 85.84 89.26 89.17 86.14
432 372 48 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 84.27 86.36 88.12 84.72 83.41 84.43 84.53 84.93 84.69 85.00 87.54 86.68 86.27 85.35 88.36 85.61 85.31 85.74 87.54 87.64 88.80 87.43 88.45 87.77 87.52
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.30 87.35 86.43 85.20 88.81 86.82 87.23 85.86 88.58 88.08 88.12 88.15 87.68 85.70 86.47 88.28 85.28 88.04 90.15 87.30 90.03 89.23 88.94 87.35 88.70
444 372 48 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 84.73 87.20 86.51 87.78 86.15 86.81 84.49 85.33 86.52 85.39 87.51 86.81 88.53 86.67 86.50 86.03 86.90 85.02 43.72 87.27 88.31 90.62 88.99 43.72 88.11
447 372 48 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 85.28 85.62 85.13 85.87 85.94 85.06 82.56 86.13 86.26 43.72 86.65 88.17 84.64 86.72 86.51 87.00 87.07 88.50 87.44 43.72 86.65 89.89 88.46 90.89 87.82
496 372 48 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 85.03 85.29 84.55 84.75 86.94 88.15 85.02 86.32 87.68 85.94 87.82 88.84 88.83 87.16 83.06 87.61 87.52 86.46 88.24 89.97 89.95 88.67 89.61 90.14 88.58
499 372 48 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 86.99 85.53 85.61 83.12 85.06 87.86 86.91 86.57 86.33 87.58 88.76 89.36 86.64 84.92 87.18 87.61 85.17 86.70 89.10 88.90 88.97 89.36 89.57 89.54 86.34
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 88.05 86.54 87.80 86.96 85.97 87.13 87.32 86.47 86.02 86.03 90.38 88.90 89.56 86.16 86.25 87.55 85.76 86.38 88.53 88.91 88.51 86.70 87.90 88.25 90.45
511 372 48 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 85.91 86.23 86.04 89.41 85.57 87.50 86.67 85.45 86.99 84.16 86.21 89.38 86.20 86.04 88.09 86.47 86.76 86.10 89.25 88.42 87.14 89.30 86.49 87.55 85.61
560 372 48 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 85.94 87.79 85.65 81.72 83.75 88.05 86.36 87.41 87.48 84.82 86.99 88.01 85.81 84.73 89.45 90.01 88.42 85.84 85.12 86.36 89.02 89.55 87.54 88.88 87.30
563 372 48 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 84.76 84.80 84.89 87.77 86.08 87.23 83.26 88.28 85.67 87.60 89.48 87.90 88.12 90.53 87.26 86.75 87.23 85.58 87.11 85.54 89.79 89.23 87.03 89.24 87.70
572 372 48 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 87.56 83.76 85.15 86.51 86.79 88.01 85.14 87.21 86.49 85.88 86.14 88.37 87.21 89.92 88.13 84.97 84.55 85.69 90.87 87.96 90.19 89.28 88.20 87.85 88.95
575 372 48 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 84.76 84.87 86.55 87.13 84.09 84.93 87.10 85.24 86.73 84.21 87.29 85.09 86.63 89.51 89.72 86.59 88.82 87.59 87.12 89.29 88.23 87.26 86.52 89.74 88.94
624 372 48 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 82.70 84.27 83.80 88.04 84.41 86.85 83.31 87.25 84.46 84.71 91.23 86.76 85.16 86.21 86.66 83.93 85.30 87.14 88.51 88.10 88.60 87.08 88.70 88.48 86.64
627 372 48 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 83.61 85.30 85.72 86.94 86.73 86.10 86.02 87.60 86.85 85.28 86.92 86.30 87.94 85.53 87.05 87.10 85.95 86.65 87.82 86.64 89.37 88.48 88.50 88.61 87.50
636 372 48 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.96 85.28 85.02 84.01 84.06 85.61 84.53 86.26 85.32 83.96 89.52 87.64 86.39 87.52 85.96 86.74 85.52 86.74 88.85 88.02 89.87 89.04 90.41 85.79 89.04
639 372 48 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 85.07 85.76 85.19 85.67 84.40 85.36 82.07 85.73 84.11 84.46 85.15 86.64 85.48 87.56 87.72 84.02 87.72 85.97 87.23 86.77 88.29 87.48 88.23 88.11 87.16
688 372 48 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 85.06 87.77 86.19 85.57 82.79 86.48 86.11 85.73 89.92 89.08 87.51 87.59 86.91 86.70 88.27 88.63 83.80 87.46 88.80 87.71 88.43 88.27 87.50 88.82 86.32
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 87.36 86.62 87.05 86.32 88.37 89.31 86.40 89.78 87.17 85.77 89.62 88.19 87.03 88.06 87.65 87.47 86.34 86.24 90.23 89.33 87.93 89.43 89.24 90.10 89.04
700 372 48 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.71 86.71 86.92 85.97 85.74 86.88 85.93 86.52 87.18 87.88 90.11 86.12 86.22 88.31 86.42 87.52 85.41 87.19 89.37 87.38 87.49 88.63 89.05 89.67 88.62
703 372 48 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 87.11 87.52 87.10 87.61 86.63 85.83 90.15 85.42 88.01 87.42 88.43 87.34 85.89 85.23 85.97 86.84 85.83 84.70 89.43 88.96 88.53 88.60 88.02 87.92 89.43
752 372 48 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 85.56 84.73 84.70 82.51 82.57 86.40 87.50 85.86 85.17 85.08 86.69 87.51 88.32 87.28 86.23 85.13 85.09 87.81 86.45 89.74 89.05 88.82 86.89 85.27 87.09
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.14 89.30 85.99 86.06 87.95 87.45 87.32 89.24 87.85 85.83 89.17 89.72 88.81 87.38 85.47 85.87 86.34 87.83 89.34 89.41 90.70 89.07 87.53 89.91 89.64
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 85.85 85.18 86.20 84.52 88.04 87.21 87.27 87.62 85.96 86.23 87.90 86.87 86.26 86.08 88.10 88.56 89.16 87.04 89.06 89.77 90.80 88.02 89.34 89.59 87.75
767 372 48 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 85.73 85.20 86.07 85.96 83.75 87.67 84.45 86.95 87.15 87.44 87.36 86.44 86.03 87.90 85.84 86.12 85.67 85.38 87.18 87.80 88.46 88.38 89.50 89.44 87.65
816 372 48 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 84.32 83.61 83.80 87.43 85.15 84.83 86.34 85.39 86.40 85.83 85.99 86.01 85.87 87.06 87.33 85.75 86.44 86.88 89.90 87.72 88.54 87.23 88.64 87.91 87.35
819 372 48 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 84.13 85.97 84.67 85.26 84.67 89.50 84.51 84.86 84.89 85.61 86.03 86.91 85.69 86.16 87.71 87.19 85.54 86.23 89.31 87.08 87.67 88.50 87.67 88.03 87.86
828 372 48 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 84.65 85.29 86.67 85.14 84.31 85.94 83.14 88.15 85.95 85.30 89.17 88.61 87.09 87.89 86.47 87.29 86.58 85.49 90.36 90.59 88.97 89.85 88.61 88.12 85.78
831 372 48 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 84.61 85.53 84.05 87.34 86.36 87.33 85.49 87.80 85.35 85.72 88.35 85.94 87.97 86.71 89.26 86.50 86.23 84.62 89.72 87.65 87.77 88.58 88.69 88.23 88.32
880 372 48 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 86.79 85.23 85.11 84.48 86.70 87.89 82.52 85.87 89.26 85.38 88.76 86.00 84.18 84.84 87.60 89.08 86.91 87.55 88.30 87.48 88.20 86.79 87.37 89.00 89.54
883 372 48 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 88.05 43.72 88.02 87.19 86.27 87.97 84.72 86.70 87.01 87.58 86.03 89.18 85.49 84.13 85.60 87.93 86.96 86.73 87.70 87.58 86.80 43.72 89.23 87.85 88.42
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 86.75 87.43 87.24 85.47 86.19 87.64 86.70 88.84 87.88 87.36 88.78 86.86 88.07 86.63 86.45 87.89 86.79 85.95 88.77 89.68 88.42 88.18 89.49 88.68 89.25
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 85.45 88.30 85.38 87.46 87.46 86.33 84.59 86.11 86.63 87.51 88.73 87.45 89.01 87.14 87.18 88.87 86.46 87.18 87.81 89.28 89.36 89.51 89.02 90.31 88.78
944 372 48 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 84.95 85.13 89.58 85.79 86.51 87.29 85.46 88.35 86.87 87.17 87.23 86.33 88.43 86.39 86.41 87.30 87.19 85.54 87.89 87.70 89.80 88.93 88.68 89.82 88.10
947 372 48 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 86.70 86.14 86.80 87.92 85.78 86.78 87.64 87.65 85.68 86.71 87.50 87.14 85.66 84.69 88.11 84.86 85.86 85.62 87.36 89.50 88.36 88.51 88.35 86.80 88.86
956 372 48 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 87.01 86.13 85.96 85.02 85.81 86.60 88.60 88.60 87.16 89.29 88.90 89.14 85.89 87.47 85.91 87.36 85.82 86.88 88.67 87.47 86.83 88.92 87.65 87.57 86.79
959 372 48 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 85.16 84.62 85.88 86.08 86.27 88.06 86.05 86.27 85.79 86.90 86.54 89.15 86.79 85.70 90.50 87.77 83.68 86.61 88.92 88.56 90.29 89.12 88.87 86.43 88.12
1008 372 48 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 85.01 86.32 85.19 86.40 83.92 87.04 86.35 85.92 87.63 85.40 87.62 91.17 87.71 85.61 88.14 87.68 86.91 87.58 89.84 88.17 89.09 88.26 87.00 89.31 85.99
1011 372 48 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 85.40 87.35 86.54 84.63 84.49 88.20 85.85 86.37 86.43 85.35 86.02 84.46 86.55 83.91 85.17 86.49 86.18 86.27 87.53 87.55 88.38 89.56 88.57 89.85 87.88
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 83.73 86.37 86.35 89.26 85.23 87.49 85.22 87.35 86.61 89.02 88.36 87.91 86.51 85.40 86.66 86.47 86.87 87.63 88.56 89.30 89.08 89.62 88.82 89.46 88.28
1023 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 84.31 86.21 86.73 87.96 85.71 90.44 87.60 86.32 87.00 88.56 86.66 89.55 87.54 86.04 86.97 88.76 86.68 86.46 88.02 87.06 88.84 87.87 89.03 87.84 87.02
1072 372 48 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 83.42 84.47 87.05 86.85 88.44 87.66 84.77 87.19 86.75 87.69 87.66 87.61 87.77 86.70 85.08 85.53 85.26 86.47 89.05 90.21 89.88 86.18 87.95 89.14 88.75
1075 372 48 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 85.87 85.27 84.84 85.99 88.01 87.73 87.68 86.52 88.28 86.04 87.69 88.04 86.14 86.80 85.35 88.91 85.01 86.67 89.85 88.34 89.38 87.77 87.84 87.45 89.35
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 88.63 88.33 87.01 86.57 89.05 88.56 87.57 87.38 89.00 86.30 87.32 89.44 87.40 88.07 86.77 89.25 85.38 87.85 87.80 89.60 89.31 88.06 87.94 89.04 90.95
1087 372 48 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 86.25 85.16 85.74 85.14 85.78 85.25 85.66 86.45 87.11 85.69 88.98 86.78 87.89 86.46 86.52 88.04 86.46 86.59 88.05 89.49 89.42 88.45 87.67 87.28 88.47
1136 372 48 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 83.09 86.29 85.57 86.00 85.64 87.40 85.05 87.94 84.60 86.62 88.61 84.68 86.77 88.28 85.14 88.57 87.85 86.96 87.69 86.76 79.64 89.24 88.30 89.15 89.68
1139 372 48 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 87.46 84.09 86.73 84.85 86.78 88.28 83.86 87.93 87.85 85.94 85.68 85.76 84.95 87.79 86.44 89.09 86.41 85.77 86.80 87.83 85.83 88.20 88.37 88.36 87.26
1148 372 48 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 86.32 86.40 86.04 84.35 82.01 84.48 85.70 84.94 87.77 86.59 89.17 89.03 84.57 84.08 84.50 86.89 86.30 85.23 86.97 87.65 87.50 90.65 87.76 90.48 87.71
1151 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.06 86.47 86.56 88.02 84.68 86.86 87.41 89.53 86.65 87.54 87.58 88.94 88.64 86.36 86.17 87.12 85.26 86.82 87.66 87.84 89.05 89.52 89.82 89.19 88.31
1200 372 48 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 83.45 85.10 84.45 89.39 86.73 86.24 84.27 86.20 85.47 84.07 87.57 87.94 85.04 85.05 86.03 85.60 86.91 85.39 87.72 87.08 88.91 87.81 87.56 87.89 87.30
1203 372 48 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 85.27 86.14 85.89 88.15 86.25 86.84 83.05 85.98 87.08 84.70 87.54 88.21 86.14 85.71 88.03 86.93 87.48 86.49 87.00 89.14 88.86 88.32 88.22 87.63 87.64
1212 372 48 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 85.33 87.10 85.61 85.53 85.11 86.70 85.83 87.46 88.08 85.44 89.38 87.39 86.52 86.25 86.46 86.00 86.18 85.19 87.98 89.57 86.26 87.26 88.45 88.36 88.29
1215 372 48 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 84.31 84.89 84.41 85.16 84.01 85.15 82.38 88.33 81.81 84.81 87.18 88.43 89.24 86.17 85.48 85.08 85.59 86.48 86.67 86.45 89.29 85.87 86.52 88.50 88.80
1264 372 48 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 85.42 86.55 84.12 84.32 83.09 87.55 83.44 88.90 87.16 87.19 87.49 87.67 86.31 85.86 85.88 88.16 86.14 86.15 88.10 90.32 90.09 87.09 86.69 88.57 88.91
1267 372 48 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 85.03 86.22 86.06 86.73 86.93 86.84 86.89 85.37 86.60 87.03 88.65 87.78 86.82 88.91 87.20 85.12 88.18 86.72 88.10 88.61 89.38 90.10 89.42 88.81 87.92
1276 372 48 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 85.24 85.31 86.48 87.06 87.37 86.50 87.60 86.88 86.03 85.51 88.64 87.50 86.32 86.46 86.86 86.19 88.12 88.78 88.59 87.53 89.51 88.74 85.83 89.44 89.70
1279 372 48 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 86.12 87.66 85.82 84.33 87.44 88.13 86.64 85.14 87.75 86.36 87.75 88.15 86.77 84.66 87.00 87.18 87.30 85.05 88.79 88.20 88.87 89.29 89.03 88.65 89.16
1328 372 48 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 85.15 88.47 85.95 62.08 85.23 86.69 86.90 84.74 87.74 85.66 86.82 89.57 88.13 87.45 87.23 86.96 87.28 84.39 87.78 88.95 87.93 88.00 89.16 85.87 83.09
1331 372 48 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 86.29 84.50 86.38 85.46 86.26 86.51 85.90 85.16 91.28 86.67 87.26 87.69 87.80 86.82 87.08 87.68 86.94 86.89 88.53 88.61 88.70 86.83 88.26 89.02 88.51
1340 372 48 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 85.83 85.42 85.28 86.84 85.37 87.83 85.21 89.57 85.70 86.23 86.49 87.10 86.56 88.86 87.27 88.28 86.03 86.35 88.17 87.33 89.33 87.90 85.35 89.23 87.44
1343 372 48 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.12 86.72 86.05 87.04 86.00 88.05 86.78 87.75 85.80 86.81 90.25 88.48 89.36 87.58 84.67 87.21 84.59 86.55 87.36 88.03 89.23 89.10 87.74 88.93 89.25
1392 372 48 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 83.67 87.20 86.32 85.24 86.04 86.72 86.72 89.13 89.22 85.78 86.08 88.47 87.48 86.01 88.10 87.25 86.70 86.39 87.37 87.09 90.09 89.14 89.56 89.38 90.02
1395 372 48 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 83.68 87.11 85.82 88.38 84.69 86.67 85.28 85.18 84.62 85.92 88.44 88.78 86.52 82.78 86.43 85.98 85.04 86.92 90.42 88.11 88.27 89.58 88.21 89.10 88.39
1404 372 48 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 85.73 84.30 85.69 89.06 84.72 87.60 85.70 85.67 85.88 86.20 87.57 87.22 86.34 86.18 86.01 87.29 84.38 89.27 87.06 88.10 87.90 86.45 89.00 87.99 86.21
1407 372 48 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 84.51 86.00 86.58 84.79 84.54 86.20 86.28 90.42 85.11 85.21 88.05 87.61 87.08 87.68 88.08 87.36 85.01 85.72 87.25 87.06 89.76 88.99 89.82 87.78 90.18
1456 372 48 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 87.95 88.06 85.77 86.94 84.89 84.84 85.72 90.33 84.09 85.96 87.61 89.63 86.48 86.65 85.43 86.41 85.54 86.09 88.69 89.12 87.57 89.69 88.75 90.49 86.91
1459 372 48 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 86.24 86.99 87.10 85.66 86.23 86.45 85.97 86.53 86.10 87.29 89.29 86.05 86.17 87.64 84.36 86.73 85.87 87.37 87.73 87.66 89.37 89.90 90.76 88.51 89.61
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 87.24 86.62 86.06 85.13 87.90 88.96 86.40 84.54 88.66 86.36 88.23 87.04 87.20 87.12 87.26 88.77 88.15 86.60 91.25 87.59 89.03 88.63 89.19 88.59 89.80
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.10 86.75 86.95 90.66 84.58 86.47 87.87 86.76 84.15 86.43 88.70 89.32 89.73 83.03 86.03 87.96 85.29 88.96 88.65 91.07 88.91 89.02 90.18 88.62 87.05
1520 372 48 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 84.70 84.38 85.96 87.38 86.13 88.15 86.74 87.18 86.23 87.70 89.02 86.91 87.33 84.89 86.05 88.13 88.09 87.59 87.23 88.21 88.98 87.57 88.23 89.92 89.03
1523 372 48 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 86.87 85.51 85.05 87.08 89.28 85.70 86.90 86.01 85.99 86.86 86.40 91.48 87.24 87.75 86.45 86.02 84.76 85.59 91.21 88.24 86.02 88.99 89.52 89.48 87.13
1532 372 48 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 85.06 86.28 85.21 85.45 86.48 87.36 84.60 88.29 85.36 86.95 87.13 87.69 85.40 88.22 84.28 89.38 85.85 86.56 87.51 88.81 88.82 86.84 89.26 87.30 88.22
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 85.42 87.50 88.68 86.42 86.05 86.21 86.95 85.50 86.01 85.47 87.91 88.15 87.77 86.70 86.32 87.15 89.90 86.77 88.74 92.23 88.88 88.54 88.37 88.51 88.18


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
48 372 48 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 91.62 93.12 92.33 91.84 91.78 91.42 89.05 90.49 93.82 91.27 91.53 90.07 92.36 93.47 90.92 92.12 92.59 92.38 89.73 89.63 92.17 90.26 90.67 92.51 89.58
51 372 48 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 93.79 92.93 96.39 91.31 94.47 92.76 91.84 94.65 94.78 93.42 90.98 92.95 93.33 94.55 93.10 92.96 94.33 94.85 94.13 90.11 93.62 92.76 92.07 92.27 92.44
60 372 48 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 92.04 93.08 93.96 93.10 94.05 48.12 93.61 93.61 93.12 92.61 93.64 88.43 48.12 48.12 92.96 93.17 92.05 48.12 94.37 91.22 93.02 92.83 90.52 91.08 93.16
63 372 48 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 91.37 92.68 95.02 93.76 91.19 93.83 92.94 92.98 91.49 92.73 91.69 91.54 93.40 91.72 93.15 93.40 93.44 94.95 94.35 92.57 93.60 93.22 93.61 92.06 92.10
112 372 48 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 92.45 94.40 95.57 90.83 94.10 92.80 94.79 94.14 94.57 94.69 93.86 91.50 94.00 93.79 94.38 93.29 94.42 93.27 92.96 93.74 93.24 92.23 91.82 92.55 92.88
115 372 48 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 92.25 92.48 93.88 93.85 93.59 92.70 92.25 91.89 93.81 92.53 92.25 93.75 92.15 92.60 92.79 93.54 93.98 94.14 93.50 91.10 92.20 92.19 92.89 93.71 91.58
124 372 48 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 90.62 94.57 91.43 93.95 94.12 91.66 93.74 94.79 92.49 93.74 89.82 91.57 94.92 93.28 92.72 92.39 93.83 94.24 93.62 91.31 91.83 91.93 92.06 93.30 93.10
127 372 48 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 92.52 92.13 94.57 93.75 95.07 92.36 93.22 92.93 95.74 93.27 94.20 90.88 94.36 96.10 89.80 93.70 94.98 93.53 94.42 92.53 92.41 92.38 90.09 91.67 89.05
176 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 93.70 90.77 48.12 92.68 93.50 90.95 93.76 95.68 93.71 95.41 94.35 92.85 93.28 95.18 93.97 93.11 91.94 93.59 92.56 92.82 89.16 93.12 91.32 92.50 91.88
179 372 48 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 93.83 92.33 94.42 94.71 93.04 93.44 92.79 93.65 93.51 94.87 92.83 94.43 95.88 95.05 93.43 94.67 94.90 95.83 91.99 91.40 92.58 93.77 94.42 91.17 93.80
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 94.18 92.37 92.74 91.60 93.47 92.76 95.05 94.40 93.53 94.32 91.30 89.92 94.38 90.84 94.74 93.32 95.51 94.95 93.46 89.46 93.61 91.50 94.72 92.34 88.71
191 372 48 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 95.45 95.32 93.71 94.66 94.81 93.26 94.94 92.30 94.45 92.96 94.53 92.14 93.05 94.79 95.92 91.75 95.29 92.56 91.74 90.64 93.44 92.09 93.72 92.41 92.95
240 372 48 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 90.85 48.12 93.81 94.55 91.63 90.96 91.56 91.09 91.87 91.28 91.84 91.55 92.89 93.80 92.79 92.75 90.85 93.92 89.83 92.52 91.03 90.67 93.69 90.17 90.28
243 372 48 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 93.64 91.79 92.43 94.00 93.20 93.30 94.16 93.83 93.64 92.82 93.71 91.60 94.06 92.38 95.69 94.35 93.49 94.93 91.83 90.75 91.24 93.64 93.81 95.58 92.66
252 372 48 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 92.25 95.66 94.35 95.08 96.12 92.22 92.57 96.26 96.11 93.91 96.08 91.79 94.14 94.25 93.98 94.67 94.46 94.75 92.37 91.79 94.47 92.98 93.86 94.08 93.68
255 372 48 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 93.31 91.41 93.40 94.39 95.17 93.78 91.33 94.81 94.04 93.72 93.97 93.50 94.18 94.37 94.96 94.56 95.27 95.12 93.57 91.46 92.47 91.53 93.58 94.55 90.26
304 372 48 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 94.39 92.08 95.38 94.40 92.78 94.01 94.48 95.20 94.47 95.03 92.89 90.93 94.75 93.59 91.18 93.83 92.26 94.94 90.78 92.14 92.57 94.28 92.90 92.92 90.11
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 93.38 94.54 91.04 95.16 92.55 89.78 95.01 94.57 94.24 93.75 93.06 91.70 95.36 93.01 92.31 92.70 95.06 94.65 91.22 92.35 93.35 91.46 94.07 91.11 90.75
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 93.60 95.97 93.82 95.03 94.34 91.42 96.37 93.64 94.94 93.94 92.39 94.10 92.99 94.44 92.59 93.36 94.86 91.57 92.36 91.99 93.16 93.25 92.37 93.11 92.66
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 94.23 91.41 91.90 95.00 94.48 91.07 94.07 94.24 93.01 93.05 92.59 94.00 94.57 94.54 94.39 95.55 91.52 92.03 92.53 93.29 93.69 93.70 91.93 92.25 91.78
368 372 48 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 92.53 93.44 94.70 92.93 95.77 92.26 94.44 95.39 94.72 94.23 94.71 93.61 94.64 93.80 94.13 93.21 94.80 94.27 93.03 93.46 91.82 92.08 92.65 93.93 91.98
371 372 48 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 93.98 93.96 94.46 95.37 95.78 91.97 93.43 95.06 95.20 94.29 94.14 93.52 94.16 93.44 94.82 95.61 94.97 94.05 93.41 92.43 94.81 92.45 94.60 95.18 91.01
380 372 48 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 94.19 93.06 93.25 93.59 92.99 92.59 94.38 94.41 93.87 93.41 91.64 92.16 97.07 97.09 92.35 93.87 93.79 95.72 92.72 92.77 92.72 90.75 93.41 92.16 91.17
383 372 48 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 94.90 94.87 92.87 92.39 95.89 92.02 95.08 93.63 93.88 95.40 92.59 92.94 92.17 95.53 94.81 93.43 94.01 92.38 90.91 91.57 94.63 93.45 92.11 93.74 93.61
432 372 48 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 91.00 94.56 91.93 94.41 95.27 92.93 94.49 91.38 91.87 96.23 91.71 93.68 94.17 94.91 93.98 93.64 92.59 92.71 93.91 89.95 88.79 93.80 92.14 91.76 91.84
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 93.23 95.13 93.87 93.51 93.99 91.78 92.51 94.02 94.74 94.74 94.23 94.73 93.46 92.87 94.22 95.55 94.09 93.76 92.65 89.88 94.25 91.83 92.81 91.55 93.28
444 372 48 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 93.79 94.99 93.71 94.28 94.21 90.24 93.45 95.98 94.81 93.07 93.14 91.27 94.35 94.68 94.15 92.62 95.22 94.52 48.12 91.77 93.15 91.15 93.79 48.12 92.43
447 372 48 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 94.84 94.85 95.33 94.95 95.47 92.66 93.35 95.54 94.83 48.12 93.80 93.65 95.52 95.06 96.34 93.75 96.51 94.30 93.97 48.12 94.90 91.74 92.62 92.89 91.84
496 372 48 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 92.61 93.44 93.05 92.75 94.01 92.72 92.37 94.55 94.04 93.62 91.18 91.52 93.63 93.32 94.16 93.75 95.24 94.09 93.52 92.41 92.92 93.93 94.50 93.23 93.49
499 372 48 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 94.16 95.80 94.15 93.46 93.07 92.44 91.87 94.40 94.42 93.42 94.29 93.33 92.08 93.99 95.05 92.34 95.92 91.79 91.93 91.92 94.02 87.90 93.58 93.21 93.06
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 93.90 95.05 92.75 94.51 93.55 92.41 94.31 94.22 95.80 94.24 91.74 93.11 92.54 94.02 94.12 92.65 96.25 94.58 92.82 92.77 94.30 93.41 93.92 94.80 92.14
511 372 48 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 94.77 93.07 95.58 92.96 94.79 91.08 94.34 95.53 91.12 93.71 91.74 93.62 91.29 94.64 93.13 92.78 93.72 95.38 91.53 91.44 92.44 92.50 91.90 93.76 93.25
560 372 48 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 92.51 94.13 94.52 90.97 89.13 92.29 92.28 93.77 91.58 95.01 92.27 93.34 90.59 94.04 94.50 93.74 94.55 92.95 92.36 92.89 91.75 92.25 91.62 93.73 92.33
563 372 48 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 94.52 93.96 92.93 93.47 94.86 92.80 94.38 94.78 93.05 93.93 92.12 91.73 93.64 93.60 94.88 93.83 95.19 95.33 92.34 93.36 92.72 94.29 92.97 91.94 93.21
572 372 48 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 95.76 95.70 91.35 91.46 94.63 93.07 94.32 94.91 92.85 94.68 92.22 92.80 93.83 95.03 93.44 94.59 95.10 95.17 92.82 92.80 92.68 92.72 91.81 93.41 90.82
575 372 48 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 93.33 91.31 92.90 92.81 93.79 92.24 94.62 92.19 92.10 93.96 92.87 92.62 94.05 94.87 93.29 93.76 93.98 93.75 91.03 90.73 91.00 91.78 92.30 93.52 90.86
624 372 48 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 92.58 89.80 93.06 91.02 92.86 91.11 93.11 93.92 93.06 90.54 90.34 93.16 90.68 94.10 94.04 89.23 93.61 89.77 90.95 89.25 93.53 93.10 91.92 91.83 89.56
627 372 48 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 92.13 92.87 91.80 92.50 91.90 91.47 92.64 94.66 93.35 95.26 92.39 92.57 93.59 94.51 93.48 94.13 95.29 91.64 91.44 87.32 93.07 90.15 93.07 89.59 90.65
636 372 48 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 93.72 94.01 95.29 92.43 87.11 93.38 91.85 92.08 90.73 94.23 91.38 88.86 94.58 94.60 93.72 92.21 93.54 91.57 92.36 89.73 92.48 93.57 90.56 92.99 92.27
639 372 48 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 91.49 94.72 93.75 93.15 91.99 94.35 92.06 90.84 93.60 92.99 93.80 92.86 96.22 91.27 93.13 94.62 90.61 90.84 92.49 89.86 91.05 93.34 92.03 94.21 92.24
688 372 48 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 90.49 92.91 91.19 95.70 91.55 91.81 90.92 93.99 90.86 91.77 89.47 91.32 92.83 93.61 91.31 93.30 93.63 89.03 92.10 92.11 92.06 92.79 92.78 92.82 91.21
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.56 93.20 95.29 93.18 92.99 91.37 94.41 93.20 94.32 90.86 93.95 90.54 92.71 93.35 92.87 93.86 96.18 92.60 91.94 93.24 91.32 93.00 93.09 91.37 93.08
700 372 48 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 94.65 92.82 93.94 93.24 90.52 92.30 92.67 91.57 94.57 91.77 94.14 92.60 93.87 92.77 93.62 94.36 93.30 94.60 92.00 92.61 92.86 92.81 92.70 93.89 93.05
703 372 48 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.77 93.02 95.00 94.53 95.51 93.75 92.66 95.00 95.04 95.54 92.81 94.04 95.04 96.19 93.64 94.31 94.31 93.97 94.14 92.27 94.22 92.93 91.82 92.53 93.92
752 372 48 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 93.05 94.46 92.46 93.47 94.87 92.45 95.95 94.78 93.60 95.81 91.03 91.15 93.84 95.20 94.40 92.95 94.21 92.49 92.93 93.14 93.55 92.69 93.05 91.99 94.32
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 93.61 93.12 93.15 95.64 93.75 91.55 94.29 95.06 94.69 93.61 89.31 91.46 93.41 94.24 92.63 94.38 95.42 95.06 93.07 92.34 90.95 91.58 93.51 92.57 91.64
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 93.48 95.77 95.11 93.67 92.00 93.08 93.46 94.52 94.74 95.38 92.83 93.64 94.15 94.13 91.96 95.01 94.00 94.14 92.87 91.59 92.54 93.34 93.11 93.46 92.97
767 372 48 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 93.80 94.13 94.10 94.51 95.42 88.63 94.41 95.14 92.36 94.10 93.54 93.61 91.99 93.13 94.25 95.30 94.66 93.98 93.09 92.56 94.03 92.50 92.19 93.17 92.27
816 372 48 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 93.69 92.36 94.49 91.29 94.69 90.96 92.91 94.32 93.03 92.47 91.07 91.60 91.42 93.33 92.41 93.62 94.52 90.13 91.86 88.54 94.09 91.86 93.19 91.94 91.57
819 372 48 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 91.29 91.99 91.43 94.57 95.01 90.15 91.79 94.91 92.43 93.78 90.83 95.36 92.11 94.51 92.19 94.37 93.87 95.35 89.37 92.00 93.23 92.39 93.42 92.68 88.95
828 372 48 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 94.15 94.89 94.60 93.15 94.63 92.69 93.90 95.30 95.13 95.79 92.11 91.28 93.11 93.72 93.83 94.94 93.50 93.38 92.98 91.56 93.08 92.70 93.38 92.98 92.77
831 372 48 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 94.24 95.28 95.42 95.97 95.39 92.12 92.32 94.50 94.90 93.29 90.99 93.20 94.22 94.32 92.77 94.49 94.90 94.86 92.92 92.36 93.65 95.77 94.34 93.01 93.88
880 372 48 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 92.37 92.88 92.78 93.26 93.87 91.27 92.76 93.14 91.91 94.97 91.88 92.55 94.69 93.24 92.87 92.71 92.56 92.92 94.31 90.42 92.69 90.94 92.52 91.51 91.83
883 372 48 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 95.11 48.12 92.83 92.39 94.44 92.91 93.37 92.19 92.35 94.78 92.83 93.52 93.87 95.26 94.74 95.20 94.83 95.32 91.41 89.77 93.12 48.12 93.12 91.84 92.18
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 93.34 91.70 92.76 95.52 94.60 93.56 92.59 89.66 92.92 94.74 90.15 90.52 91.21 94.28 94.80 93.85 94.34 92.68 92.15 92.25 90.14 92.90 92.70 92.15 93.40
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 93.70 94.89 92.13 92.22 94.31 92.87 92.55 93.17 94.58 92.86 90.26 91.63 91.28 93.82 92.72 92.85 94.41 93.53 91.30 93.39 90.67 93.59 92.90 91.86 91.81
944 372 48 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 94.74 94.33 93.38 95.63 95.22 94.09 95.05 95.23 95.06 94.59 92.54 93.23 94.30 95.02 91.99 94.46 94.85 92.67 91.98 90.35 93.54 95.18 94.39 92.19 93.28
947 372 48 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 93.86 93.94 95.74 93.23 93.09 93.37 92.18 92.94 92.05 93.20 91.61 93.58 93.94 94.23 95.14 93.54 95.58 93.42 92.59 92.70 92.79 91.39 92.96 93.00 93.73
956 372 48 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 93.45 93.32 92.03 94.89 93.06 91.31 93.31 91.71 93.79 92.18 91.19 92.41 93.41 95.07 93.59 94.27 96.05 92.30 94.01 92.87 91.43 95.60 92.89 93.16 93.05
959 372 48 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 92.78 95.67 95.50 95.80 94.38 93.63 96.40 94.32 94.58 95.30 93.42 92.88 95.90 95.60 92.79 95.37 95.69 92.68 94.14 93.38 93.41 93.55 92.48 93.43 92.79
1008 372 48 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 94.29 93.73 93.97 96.45 94.51 92.07 93.22 95.15 92.52 94.63 93.10 91.15 94.64 94.60 93.41 94.92 94.53 95.70 92.97 94.03 93.14 94.55 93.77 92.93 93.84
1011 372 48 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 92.07 96.09 94.17 95.66 94.90 91.34 94.19 95.55 93.28 94.21 93.74 93.67 92.65 96.14 95.99 95.22 95.55 93.40 93.48 93.35 93.60 93.75 93.84 93.20 93.67
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 93.96 95.67 93.92 94.53 93.34 92.91 95.05 92.34 92.96 95.16 92.88 91.60 92.47 93.61 93.45 93.16 93.49 92.94 93.48 92.31 90.62 92.68 93.93 92.42 92.49
1023 372 48 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 93.27 94.54 93.51 95.79 93.38 83.27 94.11 95.16 94.71 94.29 93.64 95.32 93.90 94.54 90.75 94.23 95.02 94.36 92.18 91.87 93.43 92.53 91.95 93.12 92.78
1072 372 48 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 92.47 94.86 94.88 95.79 94.55 91.69 91.07 91.07 93.07 92.99 92.80 93.93 94.78 94.47 93.28 94.48 92.70 94.20 92.43 92.72 93.26 94.93 92.54 92.19 93.18
1075 372 48 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 93.73 94.84 94.50 93.12 96.27 91.99 93.29 92.64 93.00 95.93 92.67 93.29 93.46 94.45 93.47 91.38 94.11 95.89 94.52 91.76 92.09 93.14 91.15 93.65 91.56
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 93.87 92.20 93.08 95.04 94.50 92.63 91.91 92.63 94.57 95.36 91.69 91.67 94.30 94.98 92.32 95.25 96.03 92.80 92.56 91.48 92.74 93.31 91.53 92.22 93.46
1087 372 48 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 92.81 93.56 93.97 95.14 94.50 92.16 94.41 93.54 93.18 93.85 92.13 91.16 94.73 93.55 94.46 96.50 94.67 93.85 92.96 93.84 93.27 92.44 93.76 93.02 91.01
1136 372 48 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 96.31 93.41 91.29 91.88 94.64 92.54 93.58 91.64 95.43 92.78 92.59 93.21 94.42 95.07 94.48 92.06 94.10 92.32 93.07 92.96 90.76 93.04 91.51 91.09 91.49
1139 372 48 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 94.38 94.97 94.38 94.00 94.40 93.33 93.33 94.56 95.31 94.41 93.51 92.93 95.01 93.02 95.86 94.28 94.55 94.15 91.36 93.13 93.28 92.03 93.57 93.50 93.21
1148 372 48 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 93.38 95.56 92.97 92.20 94.11 92.52 93.89 93.71 92.98 93.64 92.94 93.18 94.15 94.64 92.43 92.56 92.20 94.57 92.05 94.50 91.49 94.60 91.87 89.41 93.36
1151 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 93.22 93.55 96.29 93.81 95.24 93.19 94.56 94.51 93.71 94.03 93.07 90.28 96.01 94.81 93.84 95.88 93.81 94.27 91.42 92.05 91.28 93.07 94.25 92.91 92.39
1200 372 48 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 93.12 91.99 92.64 89.96 92.05 92.45 91.48 95.30 91.52 92.36 89.46 90.46 92.23 93.50 94.02 93.00 92.84 89.90 90.50 90.21 93.22 93.19 92.30 92.15 91.77
1203 372 48 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 93.31 91.84 94.48 92.90 94.10 92.17 93.23 95.22 93.17 93.93 92.26 92.18 93.30 94.97 94.59 96.20 95.72 94.25 93.56 94.01 93.80 92.22 93.98 92.01 93.06
1212 372 48 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 93.47 93.89 93.02 93.69 94.65 92.55 94.66 92.39 94.12 95.05 93.61 93.11 94.09 96.36 90.96 92.87 92.32 95.49 92.90 90.50 91.72 93.99 92.91 91.59 92.65
1215 372 48 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 90.60 93.28 93.66 94.61 94.62 92.87 93.34 92.74 93.00 93.95 91.30 91.29 94.74 92.20 93.87 94.00 93.12 93.70 93.45 91.49 93.90 92.63 92.94 91.99 92.12
1264 372 48 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 91.19 92.33 93.61 92.87 94.49 93.06 92.33 92.80 93.26 95.28 94.09 90.32 94.94 94.10 92.91 94.09 93.52 93.22 91.80 90.81 92.44 90.89 92.77 90.80 89.40
1267 372 48 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 91.28 93.61 92.79 94.22 93.33 92.53 93.71 92.84 92.55 92.59 93.75 93.30 93.17 91.98 94.46 93.54 94.39 94.65 92.24 94.79 94.34 91.69 92.14 92.31 89.58
1276 372 48 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 93.66 93.66 93.94 92.90 92.52 94.58 94.42 92.46 93.40 94.52 92.22 92.68 92.67 94.56 93.38 94.28 96.05 94.68 93.36 94.03 91.53 92.14 94.29 92.22 91.56
1279 372 48 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 93.90 92.19 92.15 92.21 92.07 92.29 93.16 91.05 93.22 94.24 93.58 92.67 93.63 93.21 94.43 92.55 94.75 94.06 92.56 90.22 91.48 90.68 91.54 92.19 90.41
1328 372 48 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 93.20 95.10 94.31 89.79 94.68 94.08 90.67 92.42 94.07 94.68 93.33 91.78 94.55 96.77 92.92 93.10 95.04 95.56 93.15 91.98 91.20 93.88 94.27 92.29 93.15
1331 372 48 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 95.17 92.94 95.50 94.29 94.75 91.81 91.93 94.22 92.19 94.23 92.72 94.38 94.83 93.78 94.69 96.40 94.28 94.48 94.05 92.38 92.07 93.06 93.69 92.84 93.95
1340 372 48 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.17 94.52 94.37 95.15 93.62 92.10 94.79 92.55 94.39 95.00 93.61 94.49 93.88 95.06 91.38 95.31 94.99 93.54 93.84 93.57 91.41 91.85 94.13 93.24 92.30
1343 372 48 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 92.93 94.49 95.22 94.23 95.29 91.12 91.39 93.12 91.73 93.48 93.75 93.69 94.20 95.65 94.05 92.48 94.63 93.77 92.39 94.41 93.37 93.84 91.86 92.54 93.42
1392 372 48 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 92.98 91.78 94.22 92.35 93.50 91.95 92.74 95.09 93.32 92.53 93.03 91.45 93.50 94.65 94.51 95.02 94.04 92.59 90.84 90.69 92.77 92.77 94.01 92.45 92.27
1395 372 48 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 94.29 94.30 95.18 95.65 95.29 92.63 93.17 95.50 92.93 95.58 93.50 85.32 94.65 95.34 95.77 94.69 95.95 95.55 92.84 93.04 93.08 95.33 92.52 94.10 91.94
1404 372 48 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 91.68 94.09 92.82 91.28 93.80 92.11 92.64 92.31 93.08 94.21 92.75 92.80 91.53 92.41 94.81 92.93 93.09 91.65 91.70 92.80 92.61 93.21 92.54 94.64 93.74
1407 372 48 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 91.38 94.04 93.95 95.93 94.36 91.23 93.83 90.61 95.15 94.01 93.04 93.50 95.15 93.75 94.00 94.33 93.84 93.39 94.01 91.62 91.99 90.60 93.01 94.60 93.20
1456 372 48 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 91.19 93.96 95.25 94.95 93.53 91.72 93.17 88.20 95.37 91.72 93.18 91.04 94.08 93.03 91.39 94.72 93.54 93.85 91.88 90.76 92.68 92.36 92.74 93.10 92.67
1459 372 48 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 94.47 94.72 93.29 93.30 92.34 92.66 91.40 93.72 92.17 94.28 91.57 92.08 93.59 93.93 92.00 95.55 95.11 92.01 93.69 91.93 93.11 92.69 93.49 92.88 91.48
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 95.51 93.72 94.33 94.43 93.34 91.22 94.64 95.07 93.99 94.61 93.87 93.91 93.78 94.33 93.36 93.08 94.88 93.56 91.40 91.16 92.88 93.94 93.49 91.78 94.08
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 93.04 94.32 95.52 91.98 95.25 92.57 94.78 93.67 93.58 95.08 92.89 91.94 91.43 95.09 92.80 94.19 93.09 94.03 92.11 90.11 93.27 94.02 92.81 92.60 93.10
1520 372 48 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 93.04 93.84 94.66 94.50 94.07 93.04 93.67 95.23 95.81 95.08 92.39 91.41 94.97 93.90 93.03 95.05 95.07 94.64 93.62 93.19 93.58 93.87 92.51 93.06 92.26
1523 372 48 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 94.35 95.04 95.11 95.30 96.06 93.08 95.21 92.99 95.05 95.90 93.02 92.23 95.29 95.80 94.87 95.78 94.41 93.82 91.70 93.52 92.77 92.20 92.98 91.74 92.81
1532 372 48 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 94.17 93.91 93.59 95.57 94.82 92.96 94.00 93.25 93.03 94.82 94.79 92.69 94.28 93.66 94.86 93.70 96.09 93.93 93.12 89.72 92.84 93.19 93.39 93.93 91.59
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 94.87 94.80 94.28 95.28 94.42 93.59 92.80 95.34 93.48 93.19 93.12 92.23 93.32 95.04 94.55 95.23 93.06 93.55 93.65 92.18 94.48 92.46 93.70 91.94 93.71
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.30 87.35 86.43 85.20 88.81 86.82 87.23 85.86 88.58 88.08 88.12 88.15 87.68 85.70 86.47 88.28 85.28 88.04 90.15 87.30 90.03 89.23 88.94 87.35 88.70
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 87.24 86.62 86.06 85.13 87.90 88.96 86.40 84.54 88.66 86.36 88.23 87.04 87.20 87.12 87.26 88.77 88.15 86.60 91.25 87.59 89.03 88.63 89.19 88.59 89.80
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.10 86.75 86.95 90.66 84.58 86.47 87.87 86.76 84.15 86.43 88.70 89.32 89.73 83.03 86.03 87.96 85.29 88.96 88.65 91.07 88.91 89.02 90.18 88.62 87.05
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 87.36 86.62 87.05 86.32 88.37 89.31 86.40 89.78 87.17 85.77 89.62 88.19 87.03 88.06 87.65 87.47 86.34 86.24 90.23 89.33 87.93 89.43 89.24 90.10 89.04
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 86.75 87.43 87.24 85.47 86.19 87.64 86.70 88.84 87.88 87.36 88.78 86.86 88.07 86.63 86.45 87.89 86.79 85.95 88.77 89.68 88.42 88.18 89.49 88.68 89.25
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 85.45 88.30 85.38 87.46 87.46 86.33 84.59 86.11 86.63 87.51 88.73 87.45 89.01 87.14 87.18 88.87 86.46 87.18 87.81 89.28 89.36 89.51 89.02 90.31 88.78
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 88.63 88.33 87.01 86.57 89.05 88.56 87.57 87.38 89.00 86.30 87.32 89.44 87.40 88.07 86.77 89.25 85.38 87.85 87.80 89.60 89.31 88.06 87.94 89.04 90.95
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 86.73 87.99 86.54 86.40 86.67 89.27 87.74 86.81 89.71 86.17 87.91 88.32 87.14 87.46 86.59 88.63 86.55 88.45 88.79 89.51 89.08 87.59 88.33 89.97 85.85
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 87.97 87.19 86.32 86.34 87.51 86.80 85.44 85.73 87.22 87.14 87.76 87.18 88.11 86.65 87.70 86.70 86.74 87.49 91.85 89.82 89.47 88.73 89.06 91.07 91.68
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 86.46 86.67 86.34 87.15 85.56 88.09 89.13 86.37 88.11 85.97 89.27 88.36 87.43 87.66 86.40 85.95 87.84 85.50 88.21 88.75 87.69 89.97 87.71 88.93 88.75
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 88.05 86.54 87.80 86.96 85.97 87.13 87.32 86.47 86.02 86.03 90.38 88.90 89.56 86.16 86.25 87.55 85.76 86.38 88.53 88.91 88.51 86.70 87.90 88.25 90.45
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 85.42 87.50 88.68 86.42 86.05 86.21 86.95 85.50 86.01 85.47 87.91 88.15 87.77 86.70 86.32 87.15 89.90 86.77 88.74 92.23 88.88 88.54 88.37 88.51 88.18
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.14 89.30 85.99 86.06 87.95 87.45 87.32 89.24 87.85 85.83 89.17 89.72 88.81 87.38 85.47 85.87 86.34 87.83 89.34 89.41 90.70 89.07 87.53 89.91 89.64
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 85.85 85.18 86.20 84.52 88.04 87.21 87.27 87.62 85.96 86.23 87.90 86.87 86.26 86.08 88.10 88.56 89.16 87.04 89.06 89.77 90.80 88.02 89.34 89.59 87.75
1151 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 86.06 86.47 86.56 88.02 84.68 86.86 87.41 89.53 86.65 87.54 87.58 88.94 88.64 86.36 86.17 87.12 85.26 86.82 87.66 87.84 89.05 89.52 89.82 89.19 88.31
176 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 87.68 86.69 43.72 84.53 83.73 86.66 85.94 87.61 86.84 87.96 87.53 88.18 86.48 85.56 87.26 86.63 86.36 87.18 87.39 86.94 89.36 89.13 84.66 88.02 87.17
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.51 88.84 86.31 85.26 86.95 87.67 86.64 88.40 87.31 88.42 88.58 87.57 87.37 83.06 84.12 89.56 85.67 87.02 88.59 90.20 89.16 88.69 90.84 88.18 88.10
Size of the All data:  (96, 28)
Size of the Sig data:  (17, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
9 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 93.23 95.13 93.87 93.51 93.99 91.78 92.51 94.02 94.74 94.74 94.23 94.73 93.46 92.87 94.22 95.55 94.09 93.76 92.65 89.88 94.25 91.83 92.81 91.55 93.28
5 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 95.51 93.72 94.33 94.43 93.34 91.22 94.64 95.07 93.99 94.61 93.87 93.91 93.78 94.33 93.36 93.08 94.88 93.56 91.40 91.16 92.88 93.94 93.49 91.78 94.08
8 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 93.04 94.32 95.52 91.98 95.25 92.57 94.78 93.67 93.58 95.08 92.89 91.94 91.43 95.09 92.80 94.19 93.09 94.03 92.11 90.11 93.27 94.02 92.81 92.60 93.10
2 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.56 93.20 95.29 93.18 92.99 91.37 94.41 93.20 94.32 90.86 93.95 90.54 92.71 93.35 92.87 93.86 96.18 92.60 91.94 93.24 91.32 93.00 93.09 91.37 93.08
6 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 93.34 91.70 92.76 95.52 94.60 93.56 92.59 89.66 92.92 94.74 90.15 90.52 91.21 94.28 94.80 93.85 94.34 92.68 92.15 92.25 90.14 92.90 92.70 92.15 93.40
7 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 93.70 94.89 92.13 92.22 94.31 92.87 92.55 93.17 94.58 92.86 90.26 91.63 91.28 93.82 92.72 92.85 94.41 93.53 91.30 93.39 90.67 93.59 92.90 91.86 91.81
0 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 93.87 92.20 93.08 95.04 94.50 92.63 91.91 92.63 94.57 95.36 91.69 91.67 94.30 94.98 92.32 95.25 96.03 92.80 92.56 91.48 92.74 93.31 91.53 92.22 93.46
4 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 93.38 94.54 91.04 95.16 92.55 89.78 95.01 94.57 94.24 93.75 93.06 91.70 95.36 93.01 92.31 92.70 95.06 94.65 91.22 92.35 93.35 91.46 94.07 91.11 90.75
3 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 93.60 95.97 93.82 95.03 94.34 91.42 96.37 93.64 94.94 93.94 92.39 94.10 92.99 94.44 92.59 93.36 94.86 91.57 92.36 91.99 93.16 93.25 92.37 93.11 92.66
13 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 94.23 91.41 91.90 95.00 94.48 91.07 94.07 94.24 93.01 93.05 92.59 94.00 94.57 94.54 94.39 95.55 91.52 92.03 92.53 93.29 93.69 93.70 91.93 92.25 91.78
10 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 93.90 95.05 92.75 94.51 93.55 92.41 94.31 94.22 95.80 94.24 91.74 93.11 92.54 94.02 94.12 92.65 96.25 94.58 92.82 92.77 94.30 93.41 93.92 94.80 92.14
12 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 94.87 94.80 94.28 95.28 94.42 93.59 92.80 95.34 93.48 93.19 93.12 92.23 93.32 95.04 94.55 95.23 93.06 93.55 93.65 92.18 94.48 92.46 93.70 91.94 93.71
1 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 93.61 93.12 93.15 95.64 93.75 91.55 94.29 95.06 94.69 93.61 89.31 91.46 93.41 94.24 92.63 94.38 95.42 95.06 93.07 92.34 90.95 91.58 93.51 92.57 91.64
11 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 93.48 95.77 95.11 93.67 92.00 93.08 93.46 94.52 94.74 95.38 92.83 93.64 94.15 94.13 91.96 95.01 94.00 94.14 92.87 91.59 92.54 93.34 93.11 93.46 92.97
14 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 93.22 93.55 96.29 93.81 95.24 93.19 94.56 94.51 93.71 94.03 93.07 90.28 96.01 94.81 93.84 95.88 93.81 94.27 91.42 92.05 91.28 93.07 94.25 92.91 92.39
16 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 93.70 90.77 48.12 92.68 93.50 90.95 93.76 95.68 93.71 95.41 94.35 92.85 93.28 95.18 93.97 93.11 91.94 93.59 92.56 92.82 89.16 93.12 91.32 92.50 91.88
15 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 94.18 92.37 92.74 91.60 93.47 92.76 95.05 94.40 93.53 94.32 91.30 89.92 94.38 90.84 94.74 93.32 95.51 94.95 93.46 89.46 93.61 91.50 94.72 92.34 88.71
Size of the test data:  (17, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.67 3.53 6.43 6.34 6.52 5.09 8.41 6.00 6.22 5.90 2.72 2.35 7.01 7.78 10.62 3.76 9.84 7.93 4.87 -0.74 4.45 2.81 3.88 4.16 0.61 1
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.94 7.57 8.57 1.32 10.67 6.10 6.91 6.91 9.43 8.65 4.19 2.62 1.70 12.06 6.77 6.23 7.80 5.07 3.46 -0.96 4.36 5.00 2.63 3.98 6.05 1
176 372 48 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.02 4.08 4.40 8.15 9.77 4.29 7.82 8.07 6.87 7.45 6.82 4.67 6.80 9.62 6.71 6.48 5.58 6.41 5.17 5.88 -0.20 3.99 6.66 4.48 4.71 1
1535 372 48 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.45 7.30 5.60 8.86 8.37 7.38 5.85 9.84 7.47 7.72 5.21 4.08 5.55 8.34 8.23 8.08 3.16 6.78 4.91 -0.05 5.60 3.92 5.33 3.43 5.53 1
319 372 48 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.77 4.74 5.56 7.85 8.92 2.98 4.94 7.87 4.90 7.08 3.32 5.64 7.14 6.88 7.99 9.60 3.68 6.53 4.32 4.54 6.00 3.73 4.22 3.32 3.03 0
1151 372 48 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.16 7.08 9.73 5.79 10.56 6.33 7.15 4.98 7.06 6.49 5.49 1.34 7.37 8.45 7.67 8.76 8.55 7.45 3.76 4.21 2.23 3.55 4.43 3.72 4.08 0
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.63 10.59 8.91 9.15 3.96 5.87 6.19 6.90 8.78 9.15 4.93 6.77 7.89 8.05 3.86 6.45 4.84 7.10 3.81 1.82 1.74 5.32 3.77 3.87 5.22 0
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.47 3.82 7.16 9.58 5.80 4.10 6.97 5.82 6.84 7.78 0.14 1.74 4.60 6.86 7.16 8.51 9.08 7.23 3.73 2.93 0.25 2.51 5.98 2.66 2.00 0
508 372 48 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.85 8.51 4.95 7.55 7.58 5.28 6.99 7.75 9.78 8.21 1.36 4.21 2.98 7.86 7.87 5.10 10.49 8.20 4.29 3.86 5.79 6.71 6.02 6.55 1.69 0
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.93 7.78 7.44 8.31 5.18 4.96 5.28 8.16 6.16 6.66 6.11 6.58 5.78 7.17 7.75 7.27 8.81 5.72 2.50 2.58 4.22 2.60 3.87 4.20 4.58 0
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.27 7.10 8.27 9.30 5.44 2.26 8.24 10.53 5.33 8.25 5.64 6.87 6.58 7.21 6.10 4.31 6.73 6.96 0.15 3.57 3.85 5.31 4.30 3.19 4.28 0
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.65 6.55 4.50 8.76 5.88 0.51 7.27 7.76 4.53 7.58 5.15 3.38 8.22 5.55 5.72 4.07 8.51 6.20 2.43 2.84 4.27 3.87 5.74 1.14 4.90 0
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.24 3.87 6.07 8.47 5.45 4.07 4.34 5.25 5.57 9.06 4.37 2.23 6.90 6.91 5.55 6.00 10.65 4.95 4.76 1.88 3.43 5.25 3.59 3.18 2.51 0
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.25 6.59 6.75 4.76 6.85 6.54 7.96 7.06 7.95 5.35 1.53 4.18 2.27 6.68 5.54 3.98 7.95 6.35 3.49 4.11 1.31 4.08 3.88 1.55 3.03 0
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.59 4.27 5.52 10.05 8.41 5.92 5.89 0.82 5.04 7.38 1.37 3.66 3.14 7.65 8.35 5.96 7.55 6.73 3.38 2.57 1.72 4.72 3.21 3.47 4.15 0
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.20 6.58 8.24 6.86 4.62 2.06 8.01 3.42 7.15 5.09 4.33 2.35 5.68 5.29 5.22 6.39 9.84 6.36 1.71 3.91 3.39 3.57 3.85 1.27 4.04 0
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.63 8.78 7.50 8.69 6.83 4.62 10.93 7.91 7.72 6.80 4.63 6.92 4.88 7.79 4.89 6.66 8.12 4.08 0.51 2.17 3.69 4.52 3.31 2.04 0.98 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_20 89.248824 1.331033
mAP_valid_zero_21 89.158235 0.822984
mAP_valid_zero_25 89.077059 0.963151
mAP_valid_zero_19 88.989412 1.242017
mAP_valid_zero_26 88.791176 1.463207
mAP_valid_zero_22 88.707059 0.813348
mAP_valid_zero_23 88.680000 1.369457
mAP_valid_zero_11 88.440588 0.827235
mAP_valid_zero_12 88.155294 0.903515
mAP_valid_zero_13 87.864118 1.003463
mAP_valid_zero_16 87.777059 1.106519
mAP_valid_zero_6 87.496471 1.013829
mAP_valid_zero_2 87.280588 1.022585
mAP_valid_zero_9 87.279412 1.360168
mAP_valid_zero_8 87.208824 1.529497
mAP_valid_zero_18 87.135294 0.901132
mAP_valid_zero_7 86.936471 1.027855
mAP_valid_zero_5 86.792353 1.553715
mAP_valid_zero_10 86.739412 0.914525
mAP_valid_zero_17 86.662941 1.367021
mAP_valid_zero 86.629412 1.131009
mAP_valid_zero_15 86.599412 0.935965
mAP_valid_zero_14 86.401176 1.465375
mAP_valid_zero_4 86.380588 1.482584
mAP_valid_zero_3 84.151765 10.446424


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_17 94.379412 1.388711
mAP_test_zero_9 94.150000 0.754826
mAP_test_zero_16 94.107059 1.112659
mAP_test_zero_10 94.068824 1.156292
mAP_test_zero_14 94.057059 1.080166
mAP_test_zero_4 94.015294 1.308057
mAP_test_zero_8 93.976471 1.375654
mAP_test_zero_7 93.945294 1.168370
mAP_test_zero_5 93.898824 0.884194
mAP_test_zero 93.730588 0.693465
mAP_test_zero_2 93.677059 1.570620
mAP_test_zero_18 93.608824 1.001498
mAP_test_zero_15 93.422941 0.953302
mAP_test_zero_13 93.422353 1.347941
average_map 93.186141 0.609950
mAP_test_zero_23 93.072353 0.939777
mAP_test_zero_22 92.910588 0.843960
mAP_test_zero_21 92.458235 1.584169
mAP_test_zero_26 92.402353 1.293448
mAP_test_zero_11 92.400000 1.477303
mAP_test_zero_25 92.383529 0.872432
mAP_test_zero_19 92.357059 0.731187
mAP_test_zero_12 92.248824 1.487308
mAP_test_zero_6 92.105882 1.062615
mAP_test_zero_20 91.902941 1.178897
mAP_test_zero_3 90.951765 11.126060
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 83.73 86.37 86.35 89.26 85.23 87.49 85.22 87.35 86.61 89.02 88.36 87.91 86.51 85.40 86.66 86.47 86.87 87.63 88.56 89.30 89.08 89.62 88.82 89.46 88.28
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 85.30 87.35 86.43 85.20 88.81 86.82 87.23 85.86 88.58 88.08 88.12 88.15 87.68 85.70 86.47 88.28 85.28 88.04 90.15 87.30 90.03 89.23 88.94 87.35 88.70
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 87.24 86.62 86.06 85.13 87.90 88.96 86.40 84.54 88.66 86.36 88.23 87.04 87.20 87.12 87.26 88.77 88.15 86.60 91.25 87.59 89.03 88.63 89.19 88.59 89.80
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 86.10 86.75 86.95 90.66 84.58 86.47 87.87 86.76 84.15 86.43 88.70 89.32 89.73 83.03 86.03 87.96 85.29 88.96 88.65 91.07 88.91 89.02 90.18 88.62 87.05
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 87.36 86.62 87.05 86.32 88.37 89.31 86.40 89.78 87.17 85.77 89.62 88.19 87.03 88.06 87.65 87.47 86.34 86.24 90.23 89.33 87.93 89.43 89.24 90.10 89.04
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 86.75 87.43 87.24 85.47 86.19 87.64 86.70 88.84 87.88 87.36 88.78 86.86 88.07 86.63 86.45 87.89 86.79 85.95 88.77 89.68 88.42 88.18 89.49 88.68 89.25
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 85.45 88.30 85.38 87.46 87.46 86.33 84.59 86.11 86.63 87.51 88.73 87.45 89.01 87.14 87.18 88.87 86.46 87.18 87.81 89.28 89.36 89.51 89.02 90.31 88.78
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 88.63 88.33 87.01 86.57 89.05 88.56 87.57 87.38 89.00 86.30 87.32 89.44 87.40 88.07 86.77 89.25 85.38 87.85 87.80 89.60 89.31 88.06 87.94 89.04 90.95
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 86.73 87.99 86.54 86.40 86.67 89.27 87.74 86.81 89.71 86.17 87.91 88.32 87.14 87.46 86.59 88.63 86.55 88.45 88.79 89.51 89.08 87.59 88.33 89.97 85.85
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 87.97 87.19 86.32 86.34 87.51 86.80 85.44 85.73 87.22 87.14 87.76 87.18 88.11 86.65 87.70 86.70 86.74 87.49 91.85 89.82 89.47 88.73 89.06 91.07 91.68
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.14 89.30 85.99 86.06 87.95 87.45 87.32 89.24 87.85 85.83 89.17 89.72 88.81 87.38 85.47 85.87 86.34 87.83 89.34 89.41 90.70 89.07 87.53 89.91 89.64
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 85.85 85.18 86.20 84.52 88.04 87.21 87.27 87.62 85.96 86.23 87.90 86.87 86.26 86.08 88.10 88.56 89.16 87.04 89.06 89.77 90.80 88.02 89.34 89.59 87.75
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.51 88.84 86.31 85.26 86.95 87.67 86.64 88.40 87.31 88.42 88.58 87.57 87.37 83.06 84.12 89.56 85.67 87.02 88.59 90.20 89.16 88.69 90.84 88.18 88.10
Size of the All data:  (96, 28)
Size of the Sig data:  (13, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
12 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 93.96 95.67 93.92 94.53 93.34 92.91 95.05 92.34 92.96 95.16 92.88 91.60 92.47 93.61 93.45 93.16 93.49 92.94 93.48 92.31 90.62 92.68 93.93 92.42 92.49
9 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 93.23 95.13 93.87 93.51 93.99 91.78 92.51 94.02 94.74 94.74 94.23 94.73 93.46 92.87 94.22 95.55 94.09 93.76 92.65 89.88 94.25 91.83 92.81 91.55 93.28
5 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 95.51 93.72 94.33 94.43 93.34 91.22 94.64 95.07 93.99 94.61 93.87 93.91 93.78 94.33 93.36 93.08 94.88 93.56 91.40 91.16 92.88 93.94 93.49 91.78 94.08
8 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 93.04 94.32 95.52 91.98 95.25 92.57 94.78 93.67 93.58 95.08 92.89 91.94 91.43 95.09 92.80 94.19 93.09 94.03 92.11 90.11 93.27 94.02 92.81 92.60 93.10
2 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.56 93.20 95.29 93.18 92.99 91.37 94.41 93.20 94.32 90.86 93.95 90.54 92.71 93.35 92.87 93.86 96.18 92.60 91.94 93.24 91.32 93.00 93.09 91.37 93.08
6 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 93.34 91.70 92.76 95.52 94.60 93.56 92.59 89.66 92.92 94.74 90.15 90.52 91.21 94.28 94.80 93.85 94.34 92.68 92.15 92.25 90.14 92.90 92.70 92.15 93.40
7 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 93.70 94.89 92.13 92.22 94.31 92.87 92.55 93.17 94.58 92.86 90.26 91.63 91.28 93.82 92.72 92.85 94.41 93.53 91.30 93.39 90.67 93.59 92.90 91.86 91.81
0 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 93.87 92.20 93.08 95.04 94.50 92.63 91.91 92.63 94.57 95.36 91.69 91.67 94.30 94.98 92.32 95.25 96.03 92.80 92.56 91.48 92.74 93.31 91.53 92.22 93.46
4 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 93.38 94.54 91.04 95.16 92.55 89.78 95.01 94.57 94.24 93.75 93.06 91.70 95.36 93.01 92.31 92.70 95.06 94.65 91.22 92.35 93.35 91.46 94.07 91.11 90.75
3 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 93.60 95.97 93.82 95.03 94.34 91.42 96.37 93.64 94.94 93.94 92.39 94.10 92.99 94.44 92.59 93.36 94.86 91.57 92.36 91.99 93.16 93.25 92.37 93.11 92.66
1 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 93.61 93.12 93.15 95.64 93.75 91.55 94.29 95.06 94.69 93.61 89.31 91.46 93.41 94.24 92.63 94.38 95.42 95.06 93.07 92.34 90.95 91.58 93.51 92.57 91.64
10 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 93.48 95.77 95.11 93.67 92.00 93.08 93.46 94.52 94.74 95.38 92.83 93.64 94.15 94.13 91.96 95.01 94.00 94.14 92.87 91.59 92.54 93.34 93.11 93.46 92.97
11 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 94.18 92.37 92.74 91.60 93.47 92.76 95.05 94.40 93.53 94.32 91.30 89.92 94.38 90.84 94.74 93.32 95.51 94.95 93.46 89.46 93.61 91.50 94.72 92.34 88.71
Size of the test data:  (13, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1471 372 48 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.94 7.57 8.57 1.32 10.67 6.10 6.91 6.91 9.43 8.65 4.19 2.62 1.70 12.06 6.77 6.23 7.80 5.07 3.46 -0.96 4.36 5.00 2.63 3.98 6.05 1
188 372 48 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.67 3.53 6.43 6.34 6.52 5.09 8.41 6.00 6.22 5.90 2.72 2.35 7.01 7.78 10.62 3.76 9.84 7.93 4.87 -0.74 4.45 2.81 3.88 4.16 0.61 1
1020 372 48 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.23 9.30 7.57 5.27 8.11 5.42 9.83 4.99 6.35 6.14 4.52 3.69 5.96 8.21 6.79 6.69 6.62 5.31 4.92 3.01 1.54 3.06 5.11 2.96 4.21 0
435 372 48 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.93 7.78 7.44 8.31 5.18 4.96 5.28 8.16 6.16 6.66 6.11 6.58 5.78 7.17 7.75 7.27 8.81 5.72 2.50 2.58 4.22 2.60 3.87 4.20 4.58 0
1468 372 48 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.27 7.10 8.27 9.30 5.44 2.26 8.24 10.53 5.33 8.25 5.64 6.87 6.58 7.21 6.10 4.31 6.73 6.96 0.15 3.57 3.85 5.31 4.30 3.19 4.28 0
691 372 48 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.20 6.58 8.24 6.86 4.62 2.06 8.01 3.42 7.15 5.09 4.33 2.35 5.68 5.29 5.22 6.39 9.84 6.36 1.71 3.91 3.39 3.57 3.85 1.27 4.04 0
892 372 48 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.59 4.27 5.52 10.05 8.41 5.92 5.89 0.82 5.04 7.38 1.37 3.66 3.14 7.65 8.35 5.96 7.55 6.73 3.38 2.57 1.72 4.72 3.21 3.47 4.15 0
895 372 48 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.25 6.59 6.75 4.76 6.85 6.54 7.96 7.06 7.95 5.35 1.53 4.18 2.27 6.68 5.54 3.98 7.95 6.35 3.49 4.11 1.31 4.08 3.88 1.55 3.03 0
1084 372 48 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.24 3.87 6.07 8.47 5.45 4.07 4.34 5.25 5.57 9.06 4.37 2.23 6.90 6.91 5.55 6.00 10.65 4.95 4.76 1.88 3.43 5.25 3.59 3.18 2.51 0
307 372 48 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.65 6.55 4.50 8.76 5.88 0.51 7.27 7.76 4.53 7.58 5.15 3.38 8.22 5.55 5.72 4.07 8.51 6.20 2.43 2.84 4.27 3.87 5.74 1.14 4.90 0
316 372 48 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.63 8.78 7.50 8.69 6.83 4.62 10.93 7.91 7.72 6.80 4.63 6.92 4.88 7.79 4.89 6.66 8.12 4.08 0.51 2.17 3.69 4.52 3.31 2.04 0.98 0
755 372 48 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.47 3.82 7.16 9.58 5.80 4.10 6.97 5.82 6.84 7.78 0.14 1.74 4.60 6.86 7.16 8.51 9.08 7.23 3.73 2.93 0.25 2.51 5.98 2.66 2.00 0
764 372 48 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.63 10.59 8.91 9.15 3.96 5.87 6.19 6.90 8.78 9.15 4.93 6.77 7.89 8.05 3.86 6.45 4.84 7.10 3.81 1.82 1.74 5.32 3.77 3.87 5.22 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_20 89.373846 0.982315
mAP_valid_zero_21 89.329231 0.804005
mAP_valid_zero_25 89.297692 1.008259
mAP_valid_zero_19 89.296154 1.239513
mAP_valid_zero_23 89.070769 0.862926
mAP_valid_zero_26 88.836154 1.541209
mAP_valid_zero_22 88.752308 0.639038
mAP_valid_zero_11 88.398462 0.621287
mAP_valid_zero_16 88.021538 1.117705
mAP_valid_zero_12 88.001538 0.983250
mAP_valid_zero_13 87.716923 1.002990
mAP_valid_zero_6 87.690769 1.029097
mAP_valid_zero_9 87.440769 1.450112
mAP_valid_zero_18 87.406154 0.856549
mAP_valid_zero_2 87.405385 1.132193
mAP_valid_zero_5 87.285385 1.332895
mAP_valid_zero_8 87.263077 1.519130
mAP_valid_zero_10 86.970769 1.042812
mAP_valid_zero_15 86.650000 1.045873
mAP_valid_zero_7 86.645385 1.023577
mAP_valid_zero_17 86.540000 1.118295
mAP_valid_zero_4 86.511538 1.736744
mAP_valid_zero_3 86.448462 0.514277
mAP_valid_zero 86.366154 1.385494
mAP_valid_zero_14 86.290769 1.652263


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_17 94.212885 1.183352
mAP_test_zero_4 94.208269 1.196104
mAP_test_zero_14 94.156923 0.951938
mAP_test_zero_16 94.035385 1.115107
mAP_test_zero_5 93.923462 1.152222
mAP_test_zero_7 93.747115 1.278725
mAP_test_zero_9 93.680192 1.088319
mAP_test_zero_13 93.643269 1.195306
mAP_test_zero_18 93.636154 1.294183
mAP_test_zero_8 93.590962 1.803475
mAP_test_zero 93.355769 1.739785
mAP_test_zero_15 93.309615 1.291480
mAP_test_zero_10 93.298077 6.501133
average_map 92.954485 0.982671
mAP_test_zero_23 92.926923 0.765326
mAP_test_zero_3 92.749038 6.429037
mAP_test_zero_21 92.640192 1.292275
mAP_test_zero_12 92.471538 1.342197
mAP_test_zero_11 92.450962 1.327039
mAP_test_zero_26 92.386154 1.157386
mAP_test_zero_2 92.102692 8.981174
mAP_test_zero_6 91.862500 1.706873
mAP_test_zero_19 91.680000 6.231033
mAP_test_zero_25 91.590385 6.184148
mAP_test_zero_22 91.165000 8.744420
mAP_test_zero_20 91.038654 6.176708


Summary using radar plot

Code
res1_valid['id'] = res1_valid.index.to_series().apply(extract_number)
res1_test['id'] = res1_test.index.to_series().apply(extract_number)



res_comb = pd.concat([res1_valid,res1_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res1_test = res1_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range1 = np.array(list(res1_valid['mean']) + list(res1_test['mean']))

categories = [str(i) for i in range(1,26)]

fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res1_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res1_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()




##############


res2_valid['id'] = res2_valid.index.to_series().apply(extract_number)
res2_test['id'] = res2_test.index.to_series().apply(extract_number)


res_comb = pd.concat([res2_valid,res2_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res2_test = res2_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res2_valid['mean']) + list(res2_test['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res2_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res2_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()

best_valid_bit_size_48 = round(res1_valid['mean'][0])
id_best_valid = res1_valid['id'][0]
best_test_bit_size_48 = list(round(res1_test.query('id == @id_best_valid')['mean'],2))[0]

best_valid_bit_size_48_mw = round(res2_valid['mean'][0])
id_best_valid = res2_valid['id'][0]
best_test_bit_size_48_mw = list(round(res2_test.query('id == @id_best_valid')['mean'],2))[0]




The results in this presentation are from two experimental designs:

The thresholding is based on fixed values between -1 and 1 on a step size of 0.1.

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
16 372 16 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 83.31 86.95 67.78 86.19 86.38 86.91 82.53 81.63 80.29 87.29 86.84 88.19 88.13 60.76 82.11 82.38 85.58 85.32 79.59 86.64 87.66 79.98 86.54 66.11 85.88
19 372 16 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 83.32 87.74 84.84 73.32 82.80 84.29 82.88 86.42 86.24 85.61 85.19 86.81 84.30 85.63 87.14 87.08 88.34 88.56 88.81 88.48 87.70 85.39 84.07 88.04 86.52
28 372 16 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 83.00 86.13 84.21 89.08 85.19 84.60 85.32 86.56 89.47 83.73 86.45 86.68 86.11 89.45 85.21 83.17 87.06 73.42 88.71 81.45 89.47 88.45 86.41 89.64 87.75
31 372 16 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 83.12 83.99 84.14 87.06 84.22 84.83 83.96 81.23 85.18 88.01 88.70 89.54 84.93 88.06 88.10 83.02 43.72 86.92 89.01 84.25 84.89 86.21 86.38 87.58 86.19
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 84.83 88.42 84.03 84.61 87.24 84.92 84.39 87.86 87.97 85.69 90.03 86.42 87.25 43.72 90.43 86.88 86.93 88.62 86.36 87.33 89.49 88.90 87.10 89.67 86.19
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.14 85.10 87.21 86.01 86.26 86.64 87.30 86.68 88.58 85.51 89.28 85.47 89.02 88.46 89.49 88.29 88.45 89.81 90.12 88.13 89.61 88.90 89.81 89.34 89.20
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 85.66 55.61 86.21 87.07 82.88 86.35 83.86 88.87 90.69 84.39 87.88 92.49 87.78 85.49 90.85 87.91 89.03 90.32 88.94 88.65 87.86 88.46 89.81 89.91 89.77
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.67 85.95 84.21 89.47 85.77 90.28 87.24 88.50 86.75 87.52 84.52 53.51 85.93 86.60 89.88 87.80 86.05 86.87 88.55 89.62 87.66 88.76 89.07 87.97 91.66
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 84.32 84.79 86.49 86.62 85.24 88.61 85.96 88.21 87.19 87.61 88.45 88.65 86.93 87.94 88.30 55.46 43.72 88.27 87.74 89.04 88.92 88.51 89.34 91.75 89.32
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 86.38 85.67 83.84 89.78 86.49 84.83 86.89 87.94 85.84 88.76 87.55 91.69 87.17 87.06 43.72 86.51 43.72 89.07 89.58 90.44 88.87 88.90 88.62 90.41 88.78
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.03 85.49 84.62 84.11 89.00 89.08 85.88 84.64 85.14 85.31 91.59 89.31 86.01 86.88 87.95 88.05 87.15 87.36 88.27 87.60 89.02 89.00 89.47 90.10 90.79
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.63 84.66 84.54 83.76 86.59 85.53 86.50 86.99 87.35 88.42 87.92 90.59 88.28 86.22 87.39 88.12 87.10 88.33 86.72 93.02 89.38 90.40 87.25 90.93 90.07
208 372 16 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 87.20 88.25 63.66 63.93 62.85 59.49 57.47 62.04 62.62 64.34 58.63 59.23 89.62 60.53 61.34 58.66 61.74 62.89 90.32 59.32 60.43 61.18 60.42 62.23 60.49
211 372 16 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 88.65 62.01 56.70 64.45 43.72 59.49 88.10 59.99 56.15 62.36 58.03 58.90 43.72 58.61 58.92 90.43 61.63 59.44 91.53 57.02 61.21 43.72 58.93 59.07 57.51
220 372 16 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 56.27 63.90 87.95 63.49 65.26 56.97 86.29 62.26 85.19 63.81 61.84 58.84 88.94 62.77 63.19 87.23 57.24 88.84 60.44 56.89 67.26 67.33 56.16 62.61 63.69
223 372 16 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 86.65 55.70 87.57 56.78 63.28 90.66 89.44 61.60 59.97 62.12 91.70 92.06 89.04 59.46 61.42 89.82 61.28 89.54 90.65 56.57 60.08 60.03 60.45 59.92 57.87
272 372 16 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 89.69 60.96 61.84 60.62 61.37 90.68 55.70 56.01 84.84 60.60 92.19 93.93 89.38 92.14 59.74 91.96 60.39 90.10 92.23 58.76 58.97 57.83 90.23 58.24 58.94
275 372 16 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 89.81 59.88 60.17 60.38 90.59 91.19 85.34 91.72 59.53 85.35 89.17 59.01 91.18 60.01 59.70 91.67 55.78 91.43 92.20 92.98 60.29 59.83 58.48 59.29 57.95
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 88.12 56.48 90.11 62.18 62.70 90.43 89.46 59.56 91.34 61.07 91.97 92.70 89.76 90.04 61.86 91.19 55.31 91.03 91.43 92.35 59.89 58.29 89.92 59.07 58.83
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 88.39 90.65 88.85 61.19 88.63 92.22 89.61 59.68 91.54 91.49 91.05 58.79 90.50 91.45 92.65 82.95 59.15 90.62 58.93 91.19 56.89 58.14 59.40 60.00 57.57
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 87.64 61.30 87.87 60.32 90.47 91.06 89.66 59.74 90.93 59.59 92.06 89.31 87.80 58.86 59.21 89.18 58.78 91.43 89.09 91.96 58.79 58.44 59.20 59.65 57.92
339 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 87.41 90.69 86.65 60.40 88.16 92.18 85.83 59.98 90.40 89.16 89.79 58.52 84.75 58.06 60.38 90.91 91.71 90.19 57.70 58.87 58.35 56.58 90.42 56.61 57.64
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 89.68 61.30 88.66 60.53 89.72 93.22 89.91 60.42 88.25 90.94 58.35 93.18 87.08 91.68 90.29 91.42 59.61 93.22 89.16 92.17 55.85 57.59 92.46 57.11 57.41
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 87.64 59.90 87.64 61.82 89.67 89.14 88.40 89.41 89.93 89.90 91.80 89.03 91.65 87.67 43.72 86.68 90.92 90.42 57.16 89.15 88.62 56.83 58.84 59.35 60.03
400 372 16 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 88.54 62.39 56.40 63.56 63.33 56.76 63.43 62.63 62.56 61.88 59.08 59.72 57.54 62.68 43.72 89.15 62.88 61.58 61.19 60.57 61.53 62.76 62.94 63.04 64.98
403 372 16 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 57.43 60.88 55.84 56.18 59.46 57.22 57.87 61.17 56.08 88.05 90.59 56.43 88.86 59.59 60.39 91.11 60.16 60.00 56.84 56.79 62.50 59.11 60.19 43.72 60.41
412 372 16 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 43.72 87.83 62.31 64.05 63.74 56.23 87.76 61.25 57.21 63.30 89.97 59.61 89.13 61.85 60.91 62.26 63.32 62.42 91.44 59.35 61.88 58.68 63.36 59.29 62.87
415 372 16 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 54.68 54.53 57.72 57.97 57.47 89.79 90.47 59.15 88.48 57.01 53.98 91.77 91.73 57.10 59.09 55.37 89.89 91.35 91.77 54.06 54.96 57.70 51.88 58.47 57.64
464 372 16 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 88.70 60.70 55.77 43.72 60.70 56.03 87.67 59.31 90.62 63.19 57.35 91.96 90.42 91.85 59.98 92.11 60.95 59.37 58.80 58.79 57.94 60.07 58.90 58.11 59.91
467 372 16 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 87.78 62.47 88.83 61.67 61.56 90.91 90.45 61.07 60.43 90.44 91.16 59.53 91.67 60.58 60.47 91.68 61.12 90.72 92.49 86.92 58.47 61.03 53.40 61.78 60.90
476 372 16 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 87.91 62.80 89.45 89.06 89.69 56.30 88.28 61.77 56.21 90.93 88.21 59.78 90.91 90.34 60.52 91.20 59.98 88.94 91.16 58.67 57.62 61.05 88.60 58.89 58.43
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 87.95 61.87 90.22 61.29 88.97 92.04 91.37 59.78 56.52 90.71 92.44 57.58 90.51 58.92 89.45 91.93 91.73 83.90 92.47 90.16 88.72 55.90 89.65 57.97 56.25
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 90.17 90.92 59.26 90.49 88.41 92.18 89.90 90.13 90.71 89.42 92.47 56.56 87.56 60.02 58.79 90.37 59.55 92.83 57.08 58.76 58.85 56.76 56.88 58.04 56.86
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 88.23 88.67 88.41 90.09 89.81 89.27 90.29 59.27 88.25 89.66 89.78 58.16 90.36 90.97 60.61 90.91 59.27 91.15 92.44 90.37 89.38 57.79 58.88 57.38 58.39
540 372 16 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 87.16 61.01 88.87 60.54 88.67 56.81 88.89 58.66 87.67 58.46 88.60 56.72 89.51 89.05 60.25 88.09 59.83 90.92 90.28 59.16 54.51 56.15 56.95 57.13 56.86
543 372 16 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 88.02 60.30 61.16 87.78 88.67 90.23 87.84 57.89 59.40 61.42 57.91 93.05 90.65 57.54 60.23 91.68 59.80 91.42 90.15 87.97 58.27 56.80 56.35 58.82 56.39
592 372 16 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 84.27 81.09 86.09 81.65 85.54 84.78 83.15 82.95 83.82 85.06 87.62 87.47 83.61 88.98 85.86 79.13 87.78 81.79 86.23 88.53 83.26 85.10 79.83 82.99 86.21
595 372 16 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 82.91 84.67 83.72 85.49 87.59 82.54 85.47 87.01 83.38 86.98 87.04 85.99 85.16 87.68 88.10 85.85 89.45 87.30 87.84 65.67 86.59 75.95 88.21 88.73 87.62
604 372 16 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.43 83.79 86.74 83.59 85.85 83.42 80.81 86.78 85.61 85.01 61.57 86.19 85.66 87.62 89.35 85.44 87.95 86.99 88.24 87.81 87.03 86.52 87.12 87.57 88.44
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 67.50 69.28 88.19 88.72 88.74 85.57 83.91 90.79 90.45 90.32 88.88 65.01 87.98 90.31 84.46 83.94 87.54 86.43 82.93 86.99 90.74 88.20 88.15 89.14 88.23
656 372 16 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 60.13 88.09 85.83 85.06 86.28 86.65 84.99 56.50 85.09 86.54 86.77 86.30 86.40 86.48 88.47 88.77 86.84 87.85 89.70 89.97 88.29 89.14 89.27 90.34 88.44
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.52 86.55 85.38 84.63 82.42 85.52 83.98 86.72 85.40 90.50 86.34 89.77 88.63 91.02 86.47 87.33 86.67 86.96 89.29 91.82 88.34 89.81 88.81 91.15 88.36
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 85.59 86.09 86.06 86.18 84.20 87.39 83.80 89.21 86.84 86.47 90.30 86.26 86.55 86.31 88.75 88.86 89.61 86.83 90.76 88.24 89.45 89.32 89.08 91.03 88.43
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.26 86.23 86.92 86.67 87.02 88.96 83.94 87.96 85.68 87.44 86.99 88.83 86.02 88.41 87.44 88.89 86.44 87.11 90.42 87.46 87.76 89.84 90.64 88.32 88.15
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 84.13 86.57 83.83 87.60 84.34 86.64 86.54 85.90 88.58 84.97 87.53 88.43 87.43 86.89 87.65 86.53 90.35 88.53 90.74 91.37 94.45 88.25 88.48 88.75 86.88
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.23 89.30 86.63 87.65 86.57 91.51 84.03 89.13 89.00 87.01 90.99 87.75 87.29 88.16 89.22 86.77 87.58 88.77 88.82 93.96 91.15 89.34 87.55 56.13 90.02
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 82.88 85.26 85.21 43.72 84.03 88.06 84.79 88.69 85.21 85.28 90.98 87.30 88.21 88.46 85.99 88.31 86.74 86.63 85.75 87.24 88.77 89.08 88.29 89.33 89.03
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 84.30 85.92 84.63 84.90 82.97 88.29 84.36 87.53 86.64 87.78 90.68 87.85 89.74 86.51 88.48 85.88 90.90 85.08 89.24 89.57 90.12 89.68 88.58 90.50 91.32
784 372 16 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 57.93 63.47 63.25 63.39 63.58 60.56 86.48 63.60 57.25 63.50 59.93 56.08 88.42 62.11 63.10 61.22 62.28 62.17 58.82 60.20 64.55 64.11 65.23 62.92 61.72
787 372 16 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 87.93 61.74 62.84 60.99 61.57 90.04 87.83 59.68 90.33 61.96 85.60 59.67 83.26 62.19 62.23 90.17 59.94 62.92 59.01 91.50 62.18 59.70 61.82 61.96 58.91
796 372 16 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 87.43 64.57 56.88 64.58 65.34 90.02 88.11 63.22 88.39 64.82 90.92 58.61 90.91 63.35 61.89 62.48 64.16 89.59 59.31 59.77 65.40 66.61 60.65 62.51 60.37
799 372 16 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 88.73 55.47 59.85 61.14 60.20 91.33 87.83 60.31 58.98 87.62 90.90 55.32 88.86 58.62 57.95 90.19 57.71 56.72 91.91 54.53 55.56 58.62 57.17 59.58 55.76
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 88.93 60.69 89.11 62.31 61.29 92.39 89.49 90.54 90.01 90.95 91.90 59.43 90.55 91.72 60.34 89.58 60.63 90.87 91.06 91.33 57.27 60.05 59.84 58.69 58.48
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 89.05 61.65 61.72 61.05 89.20 92.43 89.28 90.98 90.91 90.22 92.05 58.88 91.96 90.61 58.45 92.97 58.84 89.71 91.67 92.46 58.04 58.95 90.25 58.07 57.61
860 372 16 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 88.90 62.53 87.99 90.66 90.47 90.93 87.86 59.29 89.62 60.25 58.37 58.48 92.17 59.91 60.84 59.80 59.86 60.41 91.02 92.19 58.96 59.97 54.65 59.87 57.09
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 87.91 89.66 87.92 60.66 89.35 89.70 89.82 60.72 91.34 91.72 56.78 93.72 89.99 59.55 60.05 91.21 60.87 91.44 60.25 88.70 58.13 57.64 83.08 60.50 58.35
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.66 62.22 87.68 89.15 89.60 92.71 86.81 89.41 90.41 82.57 56.24 59.21 91.43 92.19 59.78 90.91 90.92 91.72 92.69 58.52 55.65 56.70 57.43 59.25 57.08
915 372 16 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 89.90 60.69 89.19 55.25 88.08 57.39 87.85 89.52 86.32 90.68 89.88 57.43 89.93 58.78 58.55 85.80 91.42 90.02 91.30 58.07 58.94 57.85 57.21 58.07 58.33
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.20 88.68 63.47 88.68 89.20 90.90 85.79 59.15 89.41 90.71 91.40 56.33 89.61 90.71 60.27 91.19 59.66 89.66 90.66 59.17 56.23 56.34 57.28 56.38 59.20
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 88.46 87.09 89.91 60.96 89.22 91.97 85.83 87.38 90.35 91.21 58.52 60.25 87.27 89.10 60.31 88.72 59.70 88.67 90.63 91.17 58.57 57.66 88.05 57.70 59.86
976 372 16 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 64.30 64.42 62.49 63.59 62.48 89.37 64.66 63.25 58.27 64.37 57.83 59.84 60.15 59.84 62.40 58.79 58.69 64.58 57.33 43.72 65.89 66.09 57.47 63.64 66.20
979 372 16 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 62.60 61.93 87.15 60.65 63.55 91.07 56.53 59.89 56.96 62.40 92.01 56.22 89.86 60.64 61.12 91.38 61.89 59.81 91.15 55.99 60.81 61.56 62.31 60.39 58.96
988 372 16 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 56.80 63.55 63.33 63.42 62.59 89.44 88.48 62.25 61.09 62.98 90.24 59.35 88.30 61.79 64.19 57.31 89.13 91.87 89.89 58.51 61.79 65.03 63.99 60.93 62.23
991 372 16 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 86.34 61.55 61.41 63.31 59.70 91.78 90.43 61.42 62.89 62.13 57.53 91.55 88.65 57.96 61.89 60.37 61.47 57.22 90.66 55.01 60.40 61.95 59.56 60.63 60.19
1040 372 16 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 88.89 61.87 61.98 61.42 62.74 59.13 89.46 60.32 63.03 92.13 91.40 58.59 89.81 91.97 60.77 92.84 61.27 92.13 59.04 56.06 60.51 58.34 56.97 58.34 60.46
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 88.74 61.54 56.02 60.76 90.23 91.55 90.83 89.93 88.03 90.48 92.94 92.21 92.17 90.13 60.70 90.16 91.23 61.51 91.68 58.99 60.37 59.38 91.31 59.32 59.64
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 89.24 56.29 89.18 89.89 90.07 92.20 88.39 86.86 90.51 91.39 91.67 91.40 85.96 91.69 91.75 91.73 92.33 91.14 91.92 93.30 57.34 60.20 90.91 59.53 58.61
1055 372 16 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 89.79 88.87 61.26 87.91 60.72 91.94 89.82 43.72 60.86 91.47 59.19 59.41 90.29 59.40 61.53 91.86 61.60 92.22 90.67 59.25 57.45 59.03 53.78 59.37 58.21
1104 372 16 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 88.94 89.41 88.09 60.53 89.18 58.75 90.67 58.64 90.22 90.21 56.03 55.53 91.15 91.95 58.86 86.42 58.86 91.04 58.60 56.45 57.40 59.21 58.41 58.58 59.14
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 87.39 89.69 88.72 61.07 90.19 92.22 86.85 59.25 90.69 59.55 90.25 58.05 90.35 91.92 88.77 91.27 60.30 90.42 90.62 90.63 57.06 57.47 57.67 59.67 57.11
1116 372 16 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 88.17 62.07 89.02 60.28 90.69 90.38 89.91 60.50 58.85 59.21 89.03 57.12 91.80 58.10 59.08 88.90 59.93 56.06 90.41 58.76 57.73 56.81 57.31 56.93 56.57
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 87.39 61.63 89.42 90.72 90.93 90.62 88.92 60.44 89.36 89.04 89.74 91.42 91.67 90.17 59.04 87.13 92.17 88.38 91.42 57.77 56.45 57.74 57.84 56.86 87.50
1168 372 16 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 43.72 86.61 82.98 81.68 68.79 86.52 61.33 87.47 88.01 84.65 84.05 86.96 85.02 64.27 86.83 69.19 89.09 86.49 61.20 86.18 87.60 87.23 79.69 86.08 77.73
1171 372 16 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 84.51 82.65 84.15 81.96 84.15 88.72 84.51 84.17 83.85 88.69 86.22 87.65 86.56 83.61 85.33 86.84 86.23 85.80 90.47 86.81 63.05 62.24 85.51 86.44 88.10
1180 372 16 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 83.22 64.41 84.00 87.39 63.16 88.61 84.64 84.08 85.61 84.07 87.91 90.75 81.83 60.11 62.26 86.41 87.25 85.16 88.99 88.70 88.51 87.81 87.75 82.30 81.99
1183 372 16 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 68.97 82.92 82.30 85.51 83.96 84.85 82.52 86.20 83.53 85.83 86.25 86.55 86.76 84.38 87.37 86.09 87.45 85.74 84.19 88.01 86.41 85.81 87.17 83.19 89.32
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 84.34 88.50 85.00 85.11 85.54 89.43 85.04 90.36 84.49 87.40 87.07 88.56 85.46 88.96 88.85 87.65 87.07 87.46 88.05 90.28 89.89 90.24 87.06 88.88 88.73
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 89.05 88.73 84.44 87.67 88.65 88.47 85.52 86.18 85.17 88.63 88.15 86.98 83.02 87.81 88.07 87.52 87.67 88.27 88.94 88.83 88.47 89.77 88.96 89.16 89.64
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 87.09 56.26 90.39 87.56 86.18 87.13 85.10 86.80 84.84 87.05 89.42 89.47 86.52 87.40 90.50 89.57 90.68 87.68 87.89 92.34 87.49 87.16 89.89 89.12 88.16
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 84.58 84.59 86.32 85.49 86.47 87.79 85.51 86.81 87.52 87.79 90.17 90.89 85.04 87.85 85.19 86.80 88.55 86.10 91.11 91.00 86.91 90.07 89.11 89.46 91.74
1296 372 16 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 83.64 87.25 86.17 86.01 84.04 84.35 84.32 83.76 86.34 85.06 90.10 87.14 86.00 87.57 88.43 84.72 88.75 86.13 91.93 88.54 90.19 87.55 89.01 88.92 86.52
1299 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 83.56 88.14 86.09 87.56 87.27 90.65 87.25 84.45 85.00 87.33 88.41 88.13 85.74 87.66 86.01 86.00 86.45 85.91 88.19 87.20 87.66 88.40 87.12 92.66 87.26
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.51 84.40 86.44 87.67 84.63 89.60 85.43 86.81 87.52 88.85 92.35 85.87 88.10 85.37 85.00 89.16 88.67 85.77 89.07 87.68 87.83 87.89 86.97 94.91 89.60
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.86 88.30 86.21 84.12 84.60 86.03 85.42 88.34 86.13 86.73 91.75 88.47 88.15 86.42 87.87 87.67 86.31 87.77 91.86 87.95 89.04 89.03 87.72 88.34 90.22
1360 372 16 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 65.58 58.27 63.72 62.16 66.03 61.30 57.31 62.30 63.58 56.73 58.93 59.46 56.50 60.51 62.23 89.82 64.50 61.51 59.40 61.48 61.34 65.02 61.17 63.06 60.89
1363 372 16 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 86.68 63.88 65.93 63.06 64.68 61.81 56.96 64.69 64.13 66.59 92.05 59.93 88.88 57.86 61.29 89.97 62.27 62.90 59.98 60.25 62.06 63.92 61.99 62.30 62.32
1372 372 16 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 57.86 65.78 64.76 67.98 65.03 62.65 87.90 65.15 88.33 64.51 89.80 62.55 66.01 64.79 64.42 64.11 64.40 90.16 88.78 62.84 63.24 63.25 63.21 62.42 63.53
1375 372 16 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 56.77 61.88 63.38 63.50 61.57 58.50 86.71 60.34 61.03 62.58 57.80 59.27 89.48 89.17 60.00 61.11 61.71 63.91 58.36 55.43 61.94 65.24 59.60 59.80 58.82
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 89.43 59.99 60.86 90.31 60.51 91.97 89.47 60.49 89.18 60.16 92.47 57.77 92.64 91.10 60.33 93.08 83.96 90.79 91.56 90.95 91.54 58.70 57.63 58.23 59.40
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 88.67 62.08 87.03 61.46 61.26 90.62 88.58 60.67 90.54 61.60 91.46 92.21 90.92 91.47 63.02 91.14 60.73 91.16 92.97 58.62 59.34 59.07 56.94 60.05 59.26
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 88.43 61.33 88.44 88.80 88.55 89.92 87.44 61.95 62.37 91.44 91.14 90.45 87.65 91.46 60.53 90.42 61.43 91.18 58.35 91.29 58.42 58.54 61.91 61.55 59.67
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 88.47 89.82 88.79 59.01 91.19 91.66 91.21 60.82 90.74 58.80 90.26 92.18 90.96 59.26 60.79 91.55 90.82 92.10 89.06 92.93 60.76 57.98 59.48 57.82 58.15
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 89.14 61.27 88.17 89.93 61.05 87.32 90.16 60.64 92.20 88.96 89.61 81.35 90.16 60.86 58.95 85.71 58.00 92.71 90.14 57.22 57.08 56.61 89.86 57.30 55.88
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 84.69 61.17 59.80 60.26 88.17 91.97 89.41 91.15 91.95 89.42 88.79 89.80 90.45 90.92 59.30 91.43 58.10 90.67 91.19 90.92 58.06 55.24 58.52 58.95 59.23
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 90.70 89.65 88.40 60.42 88.96 91.64 89.95 59.91 87.61 90.44 90.13 88.29 88.04 59.64 60.36 92.22 58.65 90.68 56.51 59.00 56.15 59.04 57.28 56.17 59.28
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 89.43 89.17 88.15 89.41 89.32 90.86 86.01 58.79 90.54 59.20 56.87 59.43 88.27 61.32 59.48 92.18 59.51 90.44 93.47 92.47 89.77 58.18 57.56 56.73 58.39
1552 372 16 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 86.08 61.67 63.42 62.95 61.64 57.52 88.58 60.37 63.58 57.38 55.33 55.67 89.75 57.85 88.19 50.04 59.44 61.82 58.14 58.44 58.88 63.04 62.08 53.90 59.58
1555 372 16 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 87.84 64.96 87.53 63.11 62.04 60.35 86.82 62.65 89.56 62.66 91.72 91.02 90.55 59.14 60.37 57.25 88.64 89.20 92.44 58.25 60.02 60.21 53.54 60.03 61.05
1564 372 16 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 56.48 57.80 86.59 86.95 60.66 91.31 88.38 54.71 57.75 89.61 90.40 90.80 89.08 57.76 55.06 91.24 58.57 56.12 92.22 93.17 52.31 57.73 57.41 57.25 56.02
1567 372 16 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 87.95 60.61 62.06 88.21 61.51 88.26 87.73 60.61 62.48 57.09 90.67 55.07 91.51 60.59 62.04 58.14 60.20 60.46 58.37 91.90 60.47 58.40 59.38 58.50 59.53


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
16 372 16 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 89.22 53.30 91.55 91.08 90.85 90.51 91.25 88.72 92.76 53.84 90.44 80.52 90.89 89.17 90.55 89.99 91.31 88.56 83.71 84.41 60.99 85.81 62.34 86.87 92.61
19 372 16 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 94.06 50.60 90.28 80.17 84.53 91.42 93.10 64.11 90.48 91.57 94.69 92.42 92.58 91.61 66.41 92.10 60.19 92.18 92.48 89.05 90.44 57.27 61.36 91.58 89.09
28 372 16 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 88.71 90.80 92.75 61.10 93.34 92.91 54.02 93.55 89.37 82.92 92.02 89.36 91.72 90.64 81.89 87.90 88.70 89.09 90.92 87.63 93.23 92.14 53.92 92.51 91.63
31 372 16 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 93.24 85.06 90.90 52.01 86.35 92.83 93.28 91.87 92.31 92.53 89.52 91.56 91.45 93.15 92.27 92.25 48.12 91.66 90.31 88.51 88.86 91.17 92.11 91.60 93.42
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 90.14 95.59 89.47 92.91 93.64 91.47 93.72 94.63 95.72 95.10 93.32 86.65 93.49 48.12 58.31 78.61 94.49 91.95 92.81 91.60 60.28 92.39 93.12 92.61 91.61
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 94.19 90.90 90.84 91.66 95.26 91.57 94.89 93.40 94.35 93.48 92.71 92.47 92.06 94.79 93.24 95.37 90.54 91.11 92.75 92.35 58.52 92.53 91.17 92.05 93.54
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 94.28 90.49 93.53 91.49 93.49 92.08 94.27 93.27 92.27 91.95 93.36 92.92 91.38 94.82 87.56 93.06 93.74 93.11 92.68 94.12 92.64 95.06 91.86 52.49 59.55
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 95.06 89.72 91.66 93.80 92.61 91.53 93.76 93.01 92.28 92.95 91.69 93.94 94.12 91.35 94.42 93.33 96.19 92.82 92.79 92.19 93.98 93.16 94.17 92.58 68.98
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.36 92.56 94.32 91.82 95.50 90.05 92.67 93.12 94.56 93.18 92.63 92.37 94.68 94.64 88.37 92.70 48.12 93.22 89.68 91.30 91.74 92.36 92.46 56.53 92.61
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.33 96.37 91.19 93.37 95.37 92.15 95.78 93.31 93.31 93.08 93.84 92.27 91.78 87.67 48.12 94.38 48.12 90.83 92.11 92.25 93.78 93.33 93.26 91.47 91.64
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 90.71 94.11 90.14 92.09 94.61 92.87 93.48 91.67 94.93 94.47 92.71 92.29 95.04 92.02 94.50 94.52 93.27 94.86 92.32 92.34 93.98 94.02 94.16 92.60 90.30
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 92.55 88.17 93.56 87.90 93.08 93.26 92.77 93.30 94.07 93.37 91.79 93.07 91.98 95.89 94.92 93.92 92.10 92.87 93.10 91.17 93.96 92.72 92.46 90.35 93.19
208 372 16 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 58.69 59.22 60.49 61.89 62.06 60.45 49.39 60.53 60.71 60.21 59.70 60.83 59.11 59.92 61.42 49.53 59.66 59.76 58.34 59.97 62.93 61.82 62.82 61.35 61.92
211 372 16 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 57.92 60.92 50.36 61.07 48.12 60.32 59.07 60.84 48.91 59.60 60.76 60.69 48.12 59.24 59.90 57.97 60.24 59.32 58.52 60.03 60.69 48.12 61.71 62.88 61.42
220 372 16 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 50.38 61.18 59.50 61.21 61.77 49.64 58.89 62.02 58.50 61.30 61.85 62.34 58.52 61.04 60.28 59.94 48.24 59.30 61.09 50.39 60.74 60.17 51.59 62.06 62.08
223 372 16 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 57.54 49.78 59.67 50.36 61.29 58.27 59.22 61.43 59.17 59.22 58.94 59.01 57.98 58.30 60.36 57.79 60.11 57.24 57.32 60.47 61.31 60.98 61.99 62.66 62.45
272 372 16 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 59.13 61.71 61.17 61.65 62.19 59.84 49.92 50.31 93.02 61.47 60.00 60.01 60.50 59.16 61.99 59.22 60.74 56.91 58.82 61.51 61.90 61.47 59.94 62.71 62.64
275 372 16 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 60.15 61.26 61.69 61.53 58.55 60.12 92.14 59.13 61.76 90.45 50.54 61.93 59.76 60.81 61.86 59.53 49.50 59.81 59.95 59.61 61.78 61.22 62.20 62.65 62.26
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 59.56 50.77 59.58 61.70 61.99 59.85 59.30 62.70 59.29 61.99 59.71 59.47 59.91 58.97 61.07 59.24 48.63 58.33 59.95 59.65 61.43 62.59 60.43 62.79 61.67
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 58.39 59.87 59.27 62.34 58.04 59.76 59.26 60.81 59.23 59.02 60.27 61.99 59.34 58.97 59.44 88.21 61.26 59.34 62.44 59.67 62.48 61.76 61.64 62.04 62.83
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 60.37 61.99 60.27 61.93 59.31 59.63 59.95 62.88 59.57 61.76 60.22 60.94 61.31 61.03 61.50 51.78 61.61 59.56 61.13 59.16 61.45 62.35 62.26 62.32 62.44
339 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 59.69 59.80 59.77 62.57 60.33 59.88 50.94 62.16 60.37 59.71 61.20 62.06 91.19 62.41 61.99 59.90 59.43 59.79 62.57 62.64 62.60 62.55 59.72 62.66 62.64
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 59.86 63.04 59.77 61.99 59.31 59.76 60.29 62.26 91.13 59.79 62.64 60.11 50.28 59.85 59.95 59.86 62.09 59.23 51.59 59.99 62.55 62.34 59.05 62.43 62.30
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 59.85 62.64 60.19 62.06 59.95 60.77 59.53 59.72 59.83 60.09 59.90 61.20 59.62 89.99 48.12 51.38 59.66 59.65 62.64 60.67 60.26 63.04 62.79 62.77 61.68
400 372 16 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 58.23 61.43 50.98 61.27 60.37 50.98 60.84 60.58 60.96 59.97 59.64 61.03 48.19 60.63 48.12 59.02 61.75 61.13 61.31 60.53 62.71 62.28 61.75 61.67 61.20
403 372 16 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 50.10 61.25 50.23 50.64 60.89 49.58 50.64 60.23 50.52 57.10 58.12 60.42 57.96 60.56 60.63 59.07 61.31 59.07 49.90 49.74 61.49 61.34 60.03 48.12 61.05
412 372 16 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 48.12 58.35 60.46 61.51 60.25 50.25 57.90 61.76 48.44 61.18 59.94 61.09 59.37 61.40 60.58 60.51 60.87 61.61 58.66 61.08 62.45 63.77 62.60 62.36 62.32
415 372 16 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 50.25 50.45 59.81 60.23 59.84 58.92 57.83 60.34 56.68 59.47 51.52 58.82 57.73 59.40 59.78 50.37 57.42 57.43 56.98 51.21 60.41 60.89 52.17 61.27 61.66
464 372 16 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 59.76 62.32 50.58 48.12 62.09 49.74 58.89 61.53 59.13 61.42 62.64 59.62 59.38 59.24 60.89 59.72 61.50 61.76 61.65 61.29 62.55 61.16 62.76 62.88 61.65
467 372 16 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 59.49 62.32 59.59 61.22 61.99 60.44 59.45 61.42 62.00 59.13 60.27 61.99 59.52 60.95 62.00 59.87 60.67 58.39 60.01 84.45 61.85 61.88 53.93 61.82 61.95
476 372 16 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 59.57 61.99 58.86 59.80 59.61 49.46 57.71 62.06 50.24 59.36 61.70 61.75 59.30 58.53 61.18 58.88 61.08 59.76 60.48 62.16 61.28 62.09 60.38 62.72 61.88
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 59.23 60.81 59.32 62.32 59.43 59.79 59.22 61.54 50.51 58.64 59.95 61.59 59.54 60.61 59.34 59.42 59.30 89.36 59.52 58.53 60.79 63.09 60.02 63.04 63.27
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 59.56 59.80 62.32 59.50 60.12 60.01 60.08 60.50 59.69 59.86 59.71 62.84 60.73 61.53 61.70 60.53 61.24 59.58 62.97 62.06 62.66 63.04 62.57 62.03 62.53
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 59.95 60.17 59.47 59.36 59.57 61.30 60.00 61.52 60.83 60.03 61.07 62.41 60.29 60.08 61.48 60.33 61.01 60.27 59.80 88.26 60.26 63.02 62.39 62.36 61.87
540 372 16 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 60.84 61.99 60.12 61.93 59.77 62.90 59.95 63.26 51.66 61.71 61.13 62.26 60.94 61.20 61.99 60.84 61.23 60.03 51.00 62.32 50.26 62.82 62.87 63.16 62.84
543 372 16 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 59.91 62.39 62.16 60.38 60.26 60.87 60.34 62.41 62.41 62.09 62.32 59.95 60.09 62.75 60.77 59.33 61.76 59.71 60.32 51.11 62.32 62.66 62.75 62.52 62.97
592 372 16 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 90.47 83.21 90.72 92.21 92.15 91.22 90.39 90.30 91.95 55.97 93.62 90.16 90.76 57.93 54.12 90.37 84.59 90.25 83.34 90.40 88.62 58.61 57.12 82.44 57.02
595 372 16 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 91.26 91.18 94.19 91.70 93.66 88.79 80.84 85.43 93.07 95.10 89.31 92.46 93.02 92.00 76.02 89.59 90.87 91.85 91.48 92.35 91.87 73.49 90.57 90.22 92.64
604 372 16 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 92.75 95.16 92.22 92.15 90.71 85.03 86.10 91.03 93.39 90.33 89.77 92.31 92.13 91.62 59.76 93.17 93.83 53.12 92.76 92.00 92.24 89.44 91.63 92.27 91.23
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 91.42 89.71 93.65 87.12 90.62 91.85 94.29 90.54 89.90 91.12 92.60 88.77 89.97 90.32 59.15 89.51 59.15 91.24 85.68 87.29 91.10 90.42 90.18 91.86 59.31
656 372 16 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 92.69 64.70 95.15 83.55 93.84 89.19 94.58 90.22 92.09 91.73 92.08 88.52 90.55 92.48 88.57 92.15 85.81 92.30 91.34 91.90 94.27 88.95 91.27 91.97 92.87
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.95 91.59 94.03 92.10 93.67 91.16 93.56 92.03 92.80 94.10 91.70 93.22 90.51 93.23 85.61 93.76 91.67 94.15 91.63 93.87 94.04 92.72 91.05 59.53 92.98
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 90.08 89.78 95.16 91.27 94.40 92.24 93.73 59.22 89.69 94.23 93.56 90.63 95.43 92.18 93.14 93.92 91.36 92.30 92.24 94.37 93.13 92.95 91.65 60.70 92.84
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 94.85 93.37 94.58 93.60 88.49 92.41 95.60 91.14 93.18 93.32 93.02 91.45 94.45 94.91 93.96 90.87 90.43 93.69 92.31 89.46 90.15 58.98 93.92 92.34 91.91
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 92.67 94.38 93.26 91.17 94.49 92.91 91.39 89.88 93.59 93.35 94.72 93.54 94.80 88.14 93.49 91.57 91.68 93.77 91.13 92.37 61.03 93.21 94.43 93.94 89.94
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 95.16 92.56 88.22 90.20 91.91 92.76 94.47 94.19 92.58 92.09 92.14 91.85 92.77 94.70 51.18 94.56 94.38 92.64 92.37 93.06 61.67 92.36 91.43 94.84 92.74
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 92.88 91.41 89.96 48.12 93.76 93.15 93.96 91.19 93.65 92.58 93.68 90.68 92.24 90.56 95.45 87.57 91.94 92.89 90.93 91.75 91.13 91.46 93.71 92.72 91.75
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.00 93.69 95.54 91.07 89.48 92.31 93.35 92.64 92.31 93.84 89.18 94.39 90.38 92.86 91.41 93.57 90.27 89.99 92.21 92.87 92.24 92.54 61.11 92.86 70.78
784 372 16 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 49.86 60.88 60.49 60.11 61.56 61.62 57.51 60.71 49.69 61.18 60.90 50.70 57.60 60.62 60.15 62.32 60.48 61.29 59.91 60.67 62.05 61.05 61.18 61.68 62.21
787 372 16 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 57.42 61.60 60.77 60.66 60.86 59.81 58.00 59.51 58.49 60.68 51.40 61.95 90.11 59.51 61.20 59.22 60.87 59.63 61.31 58.29 62.28 62.75 62.08 61.96 61.91
796 372 16 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 58.55 61.58 49.53 61.77 60.99 58.04 58.93 61.07 58.67 60.20 59.43 61.65 58.92 60.86 60.22 60.98 60.37 57.33 60.47 61.28 61.32 61.77 61.63 61.62 61.46
799 372 16 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 58.28 48.94 59.91 59.32 59.95 57.94 56.61 60.04 58.72 56.54 58.92 49.92 57.55 59.53 59.10 56.94 59.98 48.57 57.70 50.00 59.72 60.00 63.10 61.09 60.31
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 59.79 61.28 58.64 61.99 61.93 59.98 58.63 59.17 58.51 59.12 59.33 62.32 59.43 59.56 61.65 59.57 60.29 58.74 59.80 59.43 62.48 61.56 62.34 62.99 61.94
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 59.99 61.99 61.65 61.93 59.41 59.71 59.19 59.84 58.19 58.54 60.06 62.70 59.14 59.61 61.48 59.13 62.56 59.64 60.15 58.56 60.63 61.83 59.88 62.78 62.10
860 372 16 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 58.97 61.98 59.41 59.81 59.25 59.80 52.02 63.04 59.57 61.83 61.99 62.06 59.62 62.55 61.10 60.72 60.99 61.70 60.39 59.91 61.91 62.01 52.12 62.44 62.66
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 59.39 59.15 59.57 62.39 60.27 60.02 59.38 62.32 59.42 59.56 62.97 59.32 59.63 60.72 61.93 59.58 61.70 59.52 61.93 50.96 62.34 62.57 87.88 62.15 62.13
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 59.91 62.06 59.85 60.22 59.62 59.19 92.87 60.03 60.08 90.63 50.51 61.71 59.62 59.21 62.06 60.37 59.90 59.58 60.27 61.99 62.25 62.70 62.39 61.78 62.75
915 372 16 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 59.88 62.32 59.57 50.86 59.43 62.64 93.02 59.96 51.47 59.61 60.67 62.07 60.09 61.99 61.67 91.97 59.81 59.57 60.01 61.99 62.09 62.92 62.75 62.66 61.62
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 59.45 59.70 61.74 59.72 59.21 60.33 61.20 62.41 59.81 59.50 51.47 62.72 60.34 58.92 61.87 59.85 61.61 59.98 60.22 62.32 61.55 62.45 62.79 62.50 61.81
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.42 52.56 59.93 62.39 59.46 59.33 60.53 50.74 60.65 59.57 62.97 61.93 51.36 60.72 61.76 50.40 61.66 60.86 60.83 59.53 62.36 62.57 60.44 63.09 62.44
976 372 16 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 59.29 61.33 61.34 61.19 60.65 57.11 61.44 61.06 49.13 60.88 59.18 61.60 48.63 60.15 60.71 49.14 63.79 60.59 50.39 48.12 60.94 61.17 51.32 61.94 61.50
979 372 16 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 60.48 60.78 57.58 61.44 61.76 57.84 50.00 60.39 49.14 61.32 59.15 49.82 58.51 60.91 60.65 57.98 60.52 59.35 58.87 49.82 62.17 61.81 62.02 61.69 62.06
988 372 16 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 50.20 61.29 61.34 61.78 60.30 58.67 58.29 61.98 60.87 61.34 60.30 61.12 59.23 59.49 60.26 50.37 59.31 58.67 58.28 61.05 61.87 61.39 61.51 62.96 62.38
991 372 16 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 57.86 60.77 60.52 61.33 59.70 47.99 58.47 60.85 60.41 58.75 60.00 56.86 57.71 58.70 60.66 60.13 59.26 50.62 56.55 50.01 61.76 61.80 61.63 61.96 60.99
1040 372 16 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 59.29 61.65 61.65 61.65 61.36 61.93 59.11 61.36 61.88 59.57 60.38 61.91 59.00 58.98 61.93 58.56 61.64 58.77 62.32 61.38 61.74 62.41 62.10 62.32 61.43
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 59.62 61.93 50.73 61.93 59.34 59.86 59.41 59.86 52.41 59.37 59.68 59.80 59.67 58.37 61.11 60.27 58.97 61.45 59.96 61.99 61.22 61.92 59.43 62.46 61.81
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 59.47 49.98 58.86 60.19 60.23 59.78 57.95 51.19 59.11 59.57 60.38 60.49 52.74 60.08 59.35 58.63 58.51 59.69 59.90 59.87 62.55 60.78 59.69 61.83 62.45
1055 372 16 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 59.78 59.92 61.68 60.38 61.59 59.83 59.00 48.12 61.93 59.83 62.64 62.32 59.92 60.66 61.74 59.28 61.60 58.92 60.50 61.87 62.67 62.21 52.63 62.24 62.26
1104 372 16 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 59.04 60.27 59.46 61.70 59.75 62.64 59.57 62.34 59.52 59.55 62.97 63.04 59.77 59.62 60.89 50.93 61.77 59.12 62.71 62.32 62.90 61.76 62.26 61.93 62.12
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 60.43 59.65 59.41 61.99 59.81 59.45 60.40 62.90 59.46 61.76 60.73 62.32 60.60 59.86 52.81 59.54 61.64 59.61 60.77 60.77 62.48 62.39 62.60 62.32 62.97
1116 372 16 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.94 62.26 60.58 61.93 59.86 60.61 59.87 62.05 62.64 62.20 61.43 62.64 59.62 62.64 61.01 60.38 62.19 49.50 60.42 61.93 62.27 62.43 62.27 62.73 62.97
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 60.32 61.01 59.62 59.48 59.80 60.77 59.48 62.26 60.77 60.89 49.99 60.00 59.57 60.03 61.45 91.04 59.71 60.81 60.43 61.94 62.91 62.03 62.71 62.68 51.89
1168 372 16 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 48.12 90.56 92.71 91.27 93.16 88.44 92.28 90.24 92.52 92.41 84.56 86.40 87.33 89.62 50.95 89.78 93.52 90.78 91.15 90.95 88.54 91.25 91.96 92.29 89.59
1171 372 16 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 93.16 89.98 93.70 88.50 95.29 57.42 92.12 59.26 94.02 92.40 92.53 90.37 91.80 75.70 75.60 93.80 57.73 91.60 76.96 89.83 89.69 90.63 93.72 87.32 90.03
1180 372 16 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 91.77 91.94 92.46 92.74 89.65 92.41 94.63 59.41 93.56 92.98 94.22 52.88 90.72 93.91 89.48 92.57 92.32 58.94 90.40 88.90 92.71 92.74 59.18 90.67 55.75
1183 372 16 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 90.49 91.92 92.19 90.23 93.71 88.94 89.80 92.80 92.53 92.38 88.92 88.49 94.35 92.67 90.45 90.89 58.20 88.97 91.24 87.27 92.24 89.98 92.43 53.81 59.90
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 92.35 90.96 94.04 89.83 88.15 91.19 93.21 91.17 93.41 89.31 93.20 87.84 94.32 92.77 70.79 94.44 91.10 90.53 90.15 91.43 83.08 92.39 93.26 91.48 90.78
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 90.95 86.68 93.58 67.88 93.04 92.25 93.49 91.38 90.20 94.45 92.70 89.92 91.61 92.15 89.66 92.60 95.88 94.86 94.65 91.40 93.40 93.46 93.06 59.93 91.23
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 91.80 92.49 93.06 92.59 94.92 93.93 93.16 93.44 89.70 93.43 91.94 91.10 90.16 91.81 90.04 93.73 92.41 91.51 93.67 91.80 92.76 86.25 92.01 91.46 91.58
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 94.20 93.47 93.99 92.52 94.83 95.10 91.75 93.41 95.11 94.35 92.90 91.74 89.98 89.75 93.46 93.76 95.16 92.90 93.48 93.37 91.10 92.29 93.46 91.12 88.63
1296 372 16 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 94.60 93.94 93.65 92.35 92.43 93.48 93.65 91.89 77.31 90.65 92.09 93.45 93.81 94.04 93.52 84.88 94.88 94.63 93.08 91.34 94.16 85.82 93.25 91.45 85.43
1299 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 94.23 92.84 94.31 95.50 91.99 93.21 95.25 95.92 94.37 91.72 93.25 92.23 93.72 94.74 94.36 96.20 91.42 92.78 92.41 94.19 94.51 93.18 92.28 60.84 93.55
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.05 91.38 94.72 93.19 90.28 93.68 93.75 92.66 92.64 94.20 93.23 94.81 94.08 92.23 91.67 92.96 92.14 94.84 94.51 92.27 92.53 91.61 89.13 61.90 87.80
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.36 92.41 92.03 90.34 90.39 93.05 94.18 93.77 92.96 93.39 91.64 93.58 92.92 95.46 93.51 91.97 90.96 92.04 92.89 93.30 91.80 95.07 88.88 93.09 92.51
1360 372 16 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 61.20 48.90 60.54 60.40 60.93 61.34 49.88 60.83 60.71 50.70 60.59 59.25 49.76 59.62 61.57 59.39 61.79 59.63 59.49 61.96 62.40 61.23 62.75 61.42 62.41
1363 372 16 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 59.97 60.73 61.04 61.79 61.10 61.37 50.31 61.29 60.75 61.11 59.03 62.32 59.16 49.63 61.01 58.19 60.57 58.76 61.64 61.99 62.38 61.91 61.84 62.13 62.17
1372 372 16 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 49.11 61.59 61.38 60.99 61.73 61.47 59.39 60.01 58.65 59.75 60.49 61.65 61.10 61.00 60.76 60.65 61.59 58.57 48.75 62.06 61.81 62.12 61.83 62.03 62.23
1375 372 16 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 50.12 59.99 60.61 61.01 60.13 60.13 56.90 59.66 60.09 59.84 60.22 61.37 58.15 57.37 60.06 61.70 60.86 60.41 60.56 50.83 62.05 61.43 60.52 62.54 61.52
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 58.84 61.05 61.47 59.25 61.92 59.43 58.95 61.83 58.57 61.42 59.62 61.93 59.42 59.83 61.41 59.28 90.43 58.21 58.16 58.63 59.16 62.87 62.67 62.50 61.72
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 59.49 61.87 59.93 61.72 61.94 60.61 59.14 62.14 58.97 61.99 59.25 59.89 59.67 59.52 60.57 59.87 62.28 59.01 59.48 61.90 62.32 62.55 50.39 61.94 62.03
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 59.18 62.08 59.37 59.20 59.79 59.92 59.14 61.71 62.06 59.41 59.90 59.58 59.99 58.74 61.76 59.68 61.56 59.33 62.64 59.88 62.45 62.55 61.60 62.46 61.76
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 58.99 59.72 59.33 61.59 59.20 59.78 59.23 62.15 58.61 61.98 60.84 59.90 59.14 61.95 62.06 59.43 59.84 58.74 51.80 59.95 61.56 62.22 61.65 62.39 62.03
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 60.04 61.75 59.80 59.81 61.99 50.27 59.95 61.77 59.55 59.34 60.77 88.17 59.69 62.41 62.64 90.69 60.96 58.88 60.43 62.26 62.46 63.04 59.57 62.34 62.61
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 93.25 62.32 62.64 61.79 59.80 59.18 59.69 60.13 59.70 59.57 61.20 61.07 59.33 59.91 60.90 59.71 61.32 59.57 60.22 60.32 62.55 63.11 62.72 61.64 62.26
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 59.14 60.32 59.82 62.64 59.19 60.37 59.53 61.76 51.03 59.61 60.67 61.26 60.80 60.72 62.64 59.23 60.95 59.56 62.97 62.32 62.72 61.39 62.17 62.80 61.33
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.52 59.79 59.14 59.95 59.80 60.87 52.25 62.97 59.37 62.03 62.97 62.39 60.97 61.21 62.32 59.61 61.70 59.71 59.80 59.62 60.25 62.75 62.48 62.72 62.03
1552 372 16 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 56.79 61.64 60.38 61.10 60.45 59.50 57.68 60.34 61.32 48.94 50.75 50.24 58.48 59.44 58.31 56.28 60.48 58.35 60.30 60.28 61.13 61.90 61.11 64.42 62.86
1555 372 16 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 58.39 61.11 59.19 61.59 62.09 61.25 58.63 61.99 58.21 60.83 60.33 59.81 58.16 60.52 60.03 50.14 57.63 58.19 59.09 60.97 63.03 61.31 51.90 62.47 62.28
1564 372 16 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 50.46 57.43 56.65 55.72 60.53 58.33 57.19 52.14 49.03 57.76 58.32 59.64 57.98 59.86 48.93 57.13 58.73 58.01 58.37 58.31 50.77 59.92 61.14 60.04 60.77
1567 372 16 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 57.48 60.85 60.90 59.45 61.99 56.69 58.34 60.70 60.73 51.49 58.10 50.55 58.39 60.96 60.44 49.33 58.31 58.67 60.63 58.73 61.13 61.66 61.14 62.64 60.67
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 84.34 88.50 85.00 85.11 85.54 89.43 85.04 90.36 84.49 87.40 87.07 88.56 85.46 88.96 88.85 87.65 87.07 87.46 88.05 90.28 89.89 90.24 87.06 88.88 88.73
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 89.05 88.73 84.44 87.67 88.65 88.47 85.52 86.18 85.17 88.63 88.15 86.98 83.02 87.81 88.07 87.52 87.67 88.27 88.94 88.83 88.47 89.77 88.96 89.16 89.64
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 87.09 56.26 90.39 87.56 86.18 87.13 85.10 86.80 84.84 87.05 89.42 89.47 86.52 87.40 90.50 89.57 90.68 87.68 87.89 92.34 87.49 87.16 89.89 89.12 88.16
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 84.58 84.59 86.32 85.49 86.47 87.79 85.51 86.81 87.52 87.79 90.17 90.89 85.04 87.85 85.19 86.80 88.55 86.10 91.11 91.00 86.91 90.07 89.11 89.46 91.74
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.52 86.55 85.38 84.63 82.42 85.52 83.98 86.72 85.40 90.50 86.34 89.77 88.63 91.02 86.47 87.33 86.67 86.96 89.29 91.82 88.34 89.81 88.81 91.15 88.36
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 85.59 86.09 86.06 86.18 84.20 87.39 83.80 89.21 86.84 86.47 90.30 86.26 86.55 86.31 88.75 88.86 89.61 86.83 90.76 88.24 89.45 89.32 89.08 91.03 88.43
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.26 86.23 86.92 86.67 87.02 88.96 83.94 87.96 85.68 87.44 86.99 88.83 86.02 88.41 87.44 88.89 86.44 87.11 90.42 87.46 87.76 89.84 90.64 88.32 88.15
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 89.24 56.29 89.18 89.89 90.07 92.20 88.39 86.86 90.51 91.39 91.67 91.40 85.96 91.69 91.75 91.73 92.33 91.14 91.92 93.30 57.34 60.20 90.91 59.53 58.61
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 84.83 88.42 84.03 84.61 87.24 84.92 84.39 87.86 87.97 85.69 90.03 86.42 87.25 43.72 90.43 86.88 86.93 88.62 86.36 87.33 89.49 88.90 87.10 89.67 86.19
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.14 85.10 87.21 86.01 86.26 86.64 87.30 86.68 88.58 85.51 89.28 85.47 89.02 88.46 89.49 88.29 88.45 89.81 90.12 88.13 89.61 88.90 89.81 89.34 89.20
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 85.66 55.61 86.21 87.07 82.88 86.35 83.86 88.87 90.69 84.39 87.88 92.49 87.78 85.49 90.85 87.91 89.03 90.32 88.94 88.65 87.86 88.46 89.81 89.91 89.77
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.67 85.95 84.21 89.47 85.77 90.28 87.24 88.50 86.75 87.52 84.52 53.51 85.93 86.60 89.88 87.80 86.05 86.87 88.55 89.62 87.66 88.76 89.07 87.97 91.66
1299 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 83.56 88.14 86.09 87.56 87.27 90.65 87.25 84.45 85.00 87.33 88.41 88.13 85.74 87.66 86.01 86.00 86.45 85.91 88.19 87.20 87.66 88.40 87.12 92.66 87.26
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.51 84.40 86.44 87.67 84.63 89.60 85.43 86.81 87.52 88.85 92.35 85.87 88.10 85.37 85.00 89.16 88.67 85.77 89.07 87.68 87.83 87.89 86.97 94.91 89.60
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.86 88.30 86.21 84.12 84.60 86.03 85.42 88.34 86.13 86.73 91.75 88.47 88.15 86.42 87.87 87.67 86.31 87.77 91.86 87.95 89.04 89.03 87.72 88.34 90.22
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 84.13 86.57 83.83 87.60 84.34 86.64 86.54 85.90 88.58 84.97 87.53 88.43 87.43 86.89 87.65 86.53 90.35 88.53 90.74 91.37 94.45 88.25 88.48 88.75 86.88
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.23 89.30 86.63 87.65 86.57 91.51 84.03 89.13 89.00 87.01 90.99 87.75 87.29 88.16 89.22 86.77 87.58 88.77 88.82 93.96 91.15 89.34 87.55 56.13 90.02
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 82.88 85.26 85.21 43.72 84.03 88.06 84.79 88.69 85.21 85.28 90.98 87.30 88.21 88.46 85.99 88.31 86.74 86.63 85.75 87.24 88.77 89.08 88.29 89.33 89.03
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 84.30 85.92 84.63 84.90 82.97 88.29 84.36 87.53 86.64 87.78 90.68 87.85 89.74 86.51 88.48 85.88 90.90 85.08 89.24 89.57 90.12 89.68 88.58 90.50 91.32
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 84.32 84.79 86.49 86.62 85.24 88.61 85.96 88.21 87.19 87.61 88.45 88.65 86.93 87.94 88.30 55.46 43.72 88.27 87.74 89.04 88.92 88.51 89.34 91.75 89.32
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 86.38 85.67 83.84 89.78 86.49 84.83 86.89 87.94 85.84 88.76 87.55 91.69 87.17 87.06 43.72 86.51 43.72 89.07 89.58 90.44 88.87 88.90 88.62 90.41 88.78
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.03 85.49 84.62 84.11 89.00 89.08 85.88 84.64 85.14 85.31 91.59 89.31 86.01 86.88 87.95 88.05 87.15 87.36 88.27 87.60 89.02 89.00 89.47 90.10 90.79
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.63 84.66 84.54 83.76 86.59 85.53 86.50 86.99 87.35 88.42 87.92 90.59 88.28 86.22 87.39 88.12 87.10 88.33 86.72 93.02 89.38 90.40 87.25 90.93 90.07
Size of the All data:  (100, 28)
Size of the Sig data:  (23, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
8 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 92.35 90.96 94.04 89.83 88.15 91.19 93.21 91.17 93.41 89.31 93.20 87.84 94.32 92.77 70.79 94.44 91.10 90.53 90.15 91.43 83.08 92.39 93.26 91.48 90.78
1 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 90.95 86.68 93.58 67.88 93.04 92.25 93.49 91.38 90.20 94.45 92.70 89.92 91.61 92.15 89.66 92.60 95.88 94.86 94.65 91.40 93.40 93.46 93.06 59.93 91.23
15 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 91.80 92.49 93.06 92.59 94.92 93.93 93.16 93.44 89.70 93.43 91.94 91.10 90.16 91.81 90.04 93.73 92.41 91.51 93.67 91.80 92.76 86.25 92.01 91.46 91.58
2 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 94.20 93.47 93.99 92.52 94.83 95.10 91.75 93.41 95.11 94.35 92.90 91.74 89.98 89.75 93.46 93.76 95.16 92.90 93.48 93.37 91.10 92.29 93.46 91.12 88.63
11 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.95 91.59 94.03 92.10 93.67 91.16 93.56 92.03 92.80 94.10 91.70 93.22 90.51 93.23 85.61 93.76 91.67 94.15 91.63 93.87 94.04 92.72 91.05 59.53 92.98
4 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 90.08 89.78 95.16 91.27 94.40 92.24 93.73 59.22 89.69 94.23 93.56 90.63 95.43 92.18 93.14 93.92 91.36 92.30 92.24 94.37 93.13 92.95 91.65 60.70 92.84
10 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 94.85 93.37 94.58 93.60 88.49 92.41 95.60 91.14 93.18 93.32 93.02 91.45 94.45 94.91 93.96 90.87 90.43 93.69 92.31 89.46 90.15 58.98 93.92 92.34 91.91
22 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 59.47 49.98 58.86 60.19 60.23 59.78 57.95 51.19 59.11 59.57 60.38 60.49 52.74 60.08 59.35 58.63 58.51 59.69 59.90 59.87 62.55 60.78 59.69 61.83 62.45
18 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 90.14 95.59 89.47 92.91 93.64 91.47 93.72 94.63 95.72 95.10 93.32 86.65 93.49 48.12 58.31 78.61 94.49 91.95 92.81 91.60 60.28 92.39 93.12 92.61 91.61
0 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 94.19 90.90 90.84 91.66 95.26 91.57 94.89 93.40 94.35 93.48 92.71 92.47 92.06 94.79 93.24 95.37 90.54 91.11 92.75 92.35 58.52 92.53 91.17 92.05 93.54
16 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 94.28 90.49 93.53 91.49 93.49 92.08 94.27 93.27 92.27 91.95 93.36 92.92 91.38 94.82 87.56 93.06 93.74 93.11 92.68 94.12 92.64 95.06 91.86 52.49 59.55
17 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 95.06 89.72 91.66 93.80 92.61 91.53 93.76 93.01 92.28 92.95 91.69 93.94 94.12 91.35 94.42 93.33 96.19 92.82 92.79 92.19 93.98 93.16 94.17 92.58 68.98
14 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 94.23 92.84 94.31 95.50 91.99 93.21 95.25 95.92 94.37 91.72 93.25 92.23 93.72 94.74 94.36 96.20 91.42 92.78 92.41 94.19 94.51 93.18 92.28 60.84 93.55
7 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.05 91.38 94.72 93.19 90.28 93.68 93.75 92.66 92.64 94.20 93.23 94.81 94.08 92.23 91.67 92.96 92.14 94.84 94.51 92.27 92.53 91.61 89.13 61.90 87.80
9 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.36 92.41 92.03 90.34 90.39 93.05 94.18 93.77 92.96 93.39 91.64 93.58 92.92 95.46 93.51 91.97 90.96 92.04 92.89 93.30 91.80 95.07 88.88 93.09 92.51
6 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 92.67 94.38 93.26 91.17 94.49 92.91 91.39 89.88 93.59 93.35 94.72 93.54 94.80 88.14 93.49 91.57 91.68 93.77 91.13 92.37 61.03 93.21 94.43 93.94 89.94
13 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 95.16 92.56 88.22 90.20 91.91 92.76 94.47 94.19 92.58 92.09 92.14 91.85 92.77 94.70 51.18 94.56 94.38 92.64 92.37 93.06 61.67 92.36 91.43 94.84 92.74
19 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 92.88 91.41 89.96 48.12 93.76 93.15 93.96 91.19 93.65 92.58 93.68 90.68 92.24 90.56 95.45 87.57 91.94 92.89 90.93 91.75 91.13 91.46 93.71 92.72 91.75
5 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.00 93.69 95.54 91.07 89.48 92.31 93.35 92.64 92.31 93.84 89.18 94.39 90.38 92.86 91.41 93.57 90.27 89.99 92.21 92.87 92.24 92.54 61.11 92.86 70.78
20 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.36 92.56 94.32 91.82 95.50 90.05 92.67 93.12 94.56 93.18 92.63 92.37 94.68 94.64 88.37 92.70 48.12 93.22 89.68 91.30 91.74 92.36 92.46 56.53 92.61
21 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.33 96.37 91.19 93.37 95.37 92.15 95.78 93.31 93.31 93.08 93.84 92.27 91.78 87.67 48.12 94.38 48.12 90.83 92.11 92.25 93.78 93.33 93.26 91.47 91.64
12 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 90.71 94.11 90.14 92.09 94.61 92.87 93.48 91.67 94.93 94.47 92.71 92.29 95.04 92.02 94.50 94.52 93.27 94.86 92.32 92.34 93.98 94.02 94.16 92.60 90.30
3 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 92.55 88.17 93.56 87.90 93.08 93.26 92.77 93.30 94.07 93.37 91.79 93.07 91.98 95.89 94.92 93.92 92.10 92.87 93.10 91.17 93.96 92.72 92.46 90.35 93.19
Size of the test data:  (23, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.77 -6.31 -30.32 -29.70 -29.84 -32.42 -30.44 -35.67 -31.40 -31.82 -31.29 -30.91 -33.22 -31.61 -32.40 -33.10 -33.82 -31.45 -32.02 -33.43 5.21 0.58 -31.22 2.30 3.84 21
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.70 7.77 10.91 6.17 6.51 4.02 8.99 5.11 5.67 6.06 -1.50 6.54 0.64 6.35 2.93 7.69 -0.63 4.91 2.97 3.30 2.12 2.86 -27.47 2.36 -20.54 4
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.01 2.46 9.04 4.72 2.61 1.76 8.17 0.81 8.92 1.91 6.13 -0.72 8.86 3.81 -18.06 6.79 4.03 3.07 2.10 1.15 -6.81 2.15 6.20 2.60 2.05 3
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.62 34.88 7.32 4.42 10.61 5.73 10.41 4.40 1.58 7.56 5.48 0.43 3.60 9.33 -3.29 5.15 4.71 2.79 3.74 5.47 4.78 6.60 2.05 -37.42 -30.22 3
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.71 36.23 2.67 5.03 8.74 6.80 8.06 6.64 4.86 6.38 2.52 1.63 3.64 4.41 -0.46 4.16 1.73 3.83 5.78 -0.54 5.27 -0.91 2.12 2.34 3.42 3
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.93 3.26 1.59 2.55 5.34 1.25 10.44 5.06 3.58 5.08 1.15 4.10 5.48 6.54 -38.04 7.79 6.80 3.87 3.55 -0.90 -29.48 3.02 3.88 38.71 2.72 3
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 1.90 -2.05 9.14 -19.79 4.39 3.78 7.97 5.20 5.03 5.82 4.55 2.94 8.59 4.34 1.59 5.08 8.21 6.59 5.71 2.57 4.93 3.69 4.10 -29.23 1.59 3
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.31 7.17 5.44 8.30 6.40 6.55 9.33 6.77 7.75 9.41 3.29 0.23 6.24 4.40 -32.12 -8.27 7.56 3.33 6.45 4.27 -29.21 3.49 6.02 2.94 5.42 3
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.54 6.98 8.28 5.52 5.65 4.08 8.32 5.85 5.12 5.35 0.88 8.94 5.98 6.86 6.67 3.80 3.47 9.07 5.44 4.59 4.70 3.72 2.16 -33.01 -1.80 2
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.92 3.51 9.02 4.14 6.49 7.73 6.27 6.31 6.72 4.95 3.87 2.48 3.70 9.67 7.53 5.80 5.00 4.54 6.38 -1.85 4.58 2.32 5.21 -0.58 3.12 2
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.49 3.69 9.10 5.09 10.20 4.85 9.93 -29.99 2.85 7.76 3.26 4.37 8.88 5.87 4.39 5.06 1.75 5.47 1.48 6.13 3.68 3.63 2.57 -30.33 4.41 2
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.43 5.04 8.65 7.47 11.25 5.64 9.58 5.31 7.40 3.60 5.36 3.45 1.88 2.21 -0.86 6.43 5.00 7.19 2.34 2.05 5.70 2.91 2.24 -31.62 4.62 2
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.05 5.80 3.63 5.65 9.00 4.93 7.59 6.72 5.77 7.97 3.43 7.00 3.04 6.33 3.75 7.08 2.09 1.30 2.63 4.22 -31.09 3.63 1.36 2.71 4.34 1
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 11.59 7.14 7.66 6.93 1.47 3.45 11.66 3.18 7.50 5.88 6.03 2.62 8.43 6.50 6.52 1.98 3.99 6.58 1.89 2.00 2.39 -30.86 3.28 4.02 3.76 1
1299 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.67 4.70 8.22 7.94 4.72 2.56 8.00 11.47 9.37 4.39 4.84 4.10 7.98 7.08 8.35 10.20 4.97 6.87 4.22 6.99 6.85 4.78 5.16 -31.82 6.29 1
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.50 4.11 5.82 6.22 5.79 7.02 8.76 5.43 6.83 6.66 -0.11 5.11 4.77 9.04 5.64 4.30 4.65 4.27 1.03 5.35 2.76 6.04 1.16 4.75 2.29 1
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.54 7.81 9.43 3.57 10.15 6.27 4.85 3.98 5.01 8.38 7.19 5.11 7.37 1.25 5.84 5.04 1.33 5.24 0.39 1.00 -33.42 4.96 5.95 5.19 3.06 1
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.00 6.15 4.75 4.40 9.73 5.09 9.17 2.50 8.44 7.30 2.70 3.38 4.03 2.10 9.46 -0.74 5.20 6.26 5.18 4.51 2.36 2.38 5.42 3.39 2.72 1
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.62 8.88 7.67 7.03 8.36 7.31 6.24 6.60 7.59 6.56 2.73 0.85 4.94 1.90 8.27 6.96 6.61 6.80 2.37 2.37 4.19 2.22 4.35 1.66 -3.11 1
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.04 7.77 7.83 5.20 10.26 1.44 6.71 4.91 7.37 5.57 4.18 3.72 7.75 6.70 0.07 37.24 4.40 4.95 1.94 2.26 2.82 3.85 3.12 -35.22 3.29 1
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.68 8.62 5.52 7.98 5.61 3.79 7.60 7.03 9.79 9.16 1.12 2.98 9.03 5.14 6.55 6.47 6.12 7.50 4.05 4.74 4.96 5.02 4.69 2.50 -0.49 1
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.39 3.77 7.45 4.33 6.84 1.25 6.52 4.51 5.53 5.43 7.17 40.43 8.19 4.75 4.54 5.53 10.14 5.95 4.24 2.57 6.32 4.40 5.10 4.61 -22.68 1
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.95 10.70 7.35 3.59 8.88 7.32 8.89 5.37 7.47 4.32 6.29 0.58 4.61 0.61 4.40 7.87 4.40 1.76 2.53 1.81 4.91 4.43 4.64 1.06 2.86 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_20 89.655217 2.135358
mAP_valid_abs_values_11 89.131304 2.025645
mAP_valid_abs_values_19 89.057826 1.635459
mAP_valid_abs_values_23 88.680000 1.156248
mAP_valid_abs_values_6 87.996087 2.054004
mAP_valid_abs_values_26 87.910000 6.544522
mAP_valid_abs_values_22 87.822174 6.071457
mAP_valid_abs_values_18 87.767826 1.487316
mAP_valid_abs_values_21 87.629565 6.781426
mAP_valid_abs_values_8 87.453913 1.429039
mAP_valid_abs_values_10 87.296957 1.706470
mAP_valid_abs_values_25 87.276087 9.434357
mAP_valid_abs_values_12 87.134348 7.566842
mAP_valid_abs_values_13 86.966522 1.493454
mAP_valid_abs_values_9 86.871304 1.755372
mAP_valid_abs_values_16 86.421304 6.872286
mAP_valid_abs_values_15 86.315217 9.454895
mAP_valid_abs_values_5 85.844783 1.951053
mAP_valid_abs_values_3 85.820870 1.634909
mAP_valid_abs_values_14 85.708261 9.278572
mAP_valid_abs_values_7 85.526957 1.313200
mAP_valid_abs_values 85.295652 1.676590
mAP_valid_abs_values_4 84.689130 9.109113
mAP_valid_abs_values_17 84.268261 12.905762
mAP_valid_abs_values_2 82.470435 10.563067


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_7 92.180000 7.536976
mAP_test_abs_values_10 91.804783 7.129978
mAP_test_abs_values 91.722609 7.205630
mAP_test_abs_values_9 91.599565 7.257929
mAP_test_abs_values_5 91.460435 7.149847
mAP_test_abs_values_3 91.306522 7.345817
mAP_test_abs_values_18 91.276087 7.014224
mAP_test_abs_values_11 91.273478 6.822132
mAP_test_abs_values_16 91.130435 7.902112
mAP_test_abs_values_13 91.071304 8.520884
mAP_test_abs_values_6 91.048261 6.899788
mAP_test_abs_values_19 90.987826 6.878546
mAP_test_abs_values_20 90.986957 6.881164
mAP_test_abs_values_12 90.584783 6.836328
mAP_test_abs_values_2 90.213043 9.049217
mAP_test_abs_values_22 89.774783 9.579237
mAP_test_abs_values_23 89.640435 9.342427
average_map 89.586748 6.818341
mAP_test_abs_values_8 89.519130 10.974914
mAP_test_abs_values_14 89.342174 11.479508
mAP_test_abs_values_4 87.591739 11.918222
mAP_test_abs_values_17 87.212174 14.325746
mAP_test_abs_values_26 87.082174 10.440165
mAP_test_abs_values_21 85.391304 13.456053
mAP_test_abs_values_15 84.631304 15.268350
mAP_test_abs_values_25 80.837391 16.268674
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 67.50 69.28 88.19 88.72 88.74 85.57 83.91 90.79 90.45 90.32 88.88 65.01 87.98 90.31 84.46 83.94 87.54 86.43 82.93 86.99 90.74 88.20 88.15 89.14 88.23
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 84.34 88.50 85.00 85.11 85.54 89.43 85.04 90.36 84.49 87.40 87.07 88.56 85.46 88.96 88.85 87.65 87.07 87.46 88.05 90.28 89.89 90.24 87.06 88.88 88.73
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 89.05 88.73 84.44 87.67 88.65 88.47 85.52 86.18 85.17 88.63 88.15 86.98 83.02 87.81 88.07 87.52 87.67 88.27 88.94 88.83 88.47 89.77 88.96 89.16 89.64
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 87.09 56.26 90.39 87.56 86.18 87.13 85.10 86.80 84.84 87.05 89.42 89.47 86.52 87.40 90.50 89.57 90.68 87.68 87.89 92.34 87.49 87.16 89.89 89.12 88.16
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 84.58 84.59 86.32 85.49 86.47 87.79 85.51 86.81 87.52 87.79 90.17 90.89 85.04 87.85 85.19 86.80 88.55 86.10 91.11 91.00 86.91 90.07 89.11 89.46 91.74
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 89.43 59.99 60.86 90.31 60.51 91.97 89.47 60.49 89.18 60.16 92.47 57.77 92.64 91.10 60.33 93.08 83.96 90.79 91.56 90.95 91.54 58.70 57.63 58.23 59.40
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 88.67 62.08 87.03 61.46 61.26 90.62 88.58 60.67 90.54 61.60 91.46 92.21 90.92 91.47 63.02 91.14 60.73 91.16 92.97 58.62 59.34 59.07 56.94 60.05 59.26
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 88.43 61.33 88.44 88.80 88.55 89.92 87.44 61.95 62.37 91.44 91.14 90.45 87.65 91.46 60.53 90.42 61.43 91.18 58.35 91.29 58.42 58.54 61.91 61.55 59.67
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 88.47 89.82 88.79 59.01 91.19 91.66 91.21 60.82 90.74 58.80 90.26 92.18 90.96 59.26 60.79 91.55 90.82 92.10 89.06 92.93 60.76 57.98 59.48 57.82 58.15
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.52 86.55 85.38 84.63 82.42 85.52 83.98 86.72 85.40 90.50 86.34 89.77 88.63 91.02 86.47 87.33 86.67 86.96 89.29 91.82 88.34 89.81 88.81 91.15 88.36
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 85.59 86.09 86.06 86.18 84.20 87.39 83.80 89.21 86.84 86.47 90.30 86.26 86.55 86.31 88.75 88.86 89.61 86.83 90.76 88.24 89.45 89.32 89.08 91.03 88.43
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.26 86.23 86.92 86.67 87.02 88.96 83.94 87.96 85.68 87.44 86.99 88.83 86.02 88.41 87.44 88.89 86.44 87.11 90.42 87.46 87.76 89.84 90.64 88.32 88.15
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 88.93 60.69 89.11 62.31 61.29 92.39 89.49 90.54 90.01 90.95 91.90 59.43 90.55 91.72 60.34 89.58 60.63 90.87 91.06 91.33 57.27 60.05 59.84 58.69 58.48
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 89.05 61.65 61.72 61.05 89.20 92.43 89.28 90.98 90.91 90.22 92.05 58.88 91.96 90.61 58.45 92.97 58.84 89.71 91.67 92.46 58.04 58.95 90.25 58.07 57.61
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 87.91 89.66 87.92 60.66 89.35 89.70 89.82 60.72 91.34 91.72 56.78 93.72 89.99 59.55 60.05 91.21 60.87 91.44 60.25 88.70 58.13 57.64 83.08 60.50 58.35
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 88.74 61.54 56.02 60.76 90.23 91.55 90.83 89.93 88.03 90.48 92.94 92.21 92.17 90.13 60.70 90.16 91.23 61.51 91.68 58.99 60.37 59.38 91.31 59.32 59.64
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 89.24 56.29 89.18 89.89 90.07 92.20 88.39 86.86 90.51 91.39 91.67 91.40 85.96 91.69 91.75 91.73 92.33 91.14 91.92 93.30 57.34 60.20 90.91 59.53 58.61
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.14 85.10 87.21 86.01 86.26 86.64 87.30 86.68 88.58 85.51 89.28 85.47 89.02 88.46 89.49 88.29 88.45 89.81 90.12 88.13 89.61 88.90 89.81 89.34 89.20
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 85.66 55.61 86.21 87.07 82.88 86.35 83.86 88.87 90.69 84.39 87.88 92.49 87.78 85.49 90.85 87.91 89.03 90.32 88.94 88.65 87.86 88.46 89.81 89.91 89.77
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.67 85.95 84.21 89.47 85.77 90.28 87.24 88.50 86.75 87.52 84.52 53.51 85.93 86.60 89.88 87.80 86.05 86.87 88.55 89.62 87.66 88.76 89.07 87.97 91.66
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 88.12 56.48 90.11 62.18 62.70 90.43 89.46 59.56 91.34 61.07 91.97 92.70 89.76 90.04 61.86 91.19 55.31 91.03 91.43 92.35 59.89 58.29 89.92 59.07 58.83
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 88.39 90.65 88.85 61.19 88.63 92.22 89.61 59.68 91.54 91.49 91.05 58.79 90.50 91.45 92.65 82.95 59.15 90.62 58.93 91.19 56.89 58.14 59.40 60.00 57.57
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 87.95 61.87 90.22 61.29 88.97 92.04 91.37 59.78 56.52 90.71 92.44 57.58 90.51 58.92 89.45 91.93 91.73 83.90 92.47 90.16 88.72 55.90 89.65 57.97 56.25
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.51 84.40 86.44 87.67 84.63 89.60 85.43 86.81 87.52 88.85 92.35 85.87 88.10 85.37 85.00 89.16 88.67 85.77 89.07 87.68 87.83 87.89 86.97 94.91 89.60
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.86 88.30 86.21 84.12 84.60 86.03 85.42 88.34 86.13 86.73 91.75 88.47 88.15 86.42 87.87 87.67 86.31 87.77 91.86 87.95 89.04 89.03 87.72 88.34 90.22
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 89.14 61.27 88.17 89.93 61.05 87.32 90.16 60.64 92.20 88.96 89.61 81.35 90.16 60.86 58.95 85.71 58.00 92.71 90.14 57.22 57.08 56.61 89.86 57.30 55.88
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 84.69 61.17 59.80 60.26 88.17 91.97 89.41 91.15 91.95 89.42 88.79 89.80 90.45 90.92 59.30 91.43 58.10 90.67 91.19 90.92 58.06 55.24 58.52 58.95 59.23
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 90.70 89.65 88.40 60.42 88.96 91.64 89.95 59.91 87.61 90.44 90.13 88.29 88.04 59.64 60.36 92.22 58.65 90.68 56.51 59.00 56.15 59.04 57.28 56.17 59.28
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 89.43 89.17 88.15 89.41 89.32 90.86 86.01 58.79 90.54 59.20 56.87 59.43 88.27 61.32 59.48 92.18 59.51 90.44 93.47 92.47 89.77 58.18 57.56 56.73 58.39
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 84.13 86.57 83.83 87.60 84.34 86.64 86.54 85.90 88.58 84.97 87.53 88.43 87.43 86.89 87.65 86.53 90.35 88.53 90.74 91.37 94.45 88.25 88.48 88.75 86.88
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.23 89.30 86.63 87.65 86.57 91.51 84.03 89.13 89.00 87.01 90.99 87.75 87.29 88.16 89.22 86.77 87.58 88.77 88.82 93.96 91.15 89.34 87.55 56.13 90.02
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 84.30 85.92 84.63 84.90 82.97 88.29 84.36 87.53 86.64 87.78 90.68 87.85 89.74 86.51 88.48 85.88 90.90 85.08 89.24 89.57 90.12 89.68 88.58 90.50 91.32
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.66 62.22 87.68 89.15 89.60 92.71 86.81 89.41 90.41 82.57 56.24 59.21 91.43 92.19 59.78 90.91 90.92 91.72 92.69 58.52 55.65 56.70 57.43 59.25 57.08
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.20 88.68 63.47 88.68 89.20 90.90 85.79 59.15 89.41 90.71 91.40 56.33 89.61 90.71 60.27 91.19 59.66 89.66 90.66 59.17 56.23 56.34 57.28 56.38 59.20
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 88.46 87.09 89.91 60.96 89.22 91.97 85.83 87.38 90.35 91.21 58.52 60.25 87.27 89.10 60.31 88.72 59.70 88.67 90.63 91.17 58.57 57.66 88.05 57.70 59.86
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 87.39 89.69 88.72 61.07 90.19 92.22 86.85 59.25 90.69 59.55 90.25 58.05 90.35 91.92 88.77 91.27 60.30 90.42 90.62 90.63 57.06 57.47 57.67 59.67 57.11
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 87.39 61.63 89.42 90.72 90.93 90.62 88.92 60.44 89.36 89.04 89.74 91.42 91.67 90.17 59.04 87.13 92.17 88.38 91.42 57.77 56.45 57.74 57.84 56.86 87.50
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 84.32 84.79 86.49 86.62 85.24 88.61 85.96 88.21 87.19 87.61 88.45 88.65 86.93 87.94 88.30 55.46 43.72 88.27 87.74 89.04 88.92 88.51 89.34 91.75 89.32
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 86.38 85.67 83.84 89.78 86.49 84.83 86.89 87.94 85.84 88.76 87.55 91.69 87.17 87.06 43.72 86.51 43.72 89.07 89.58 90.44 88.87 88.90 88.62 90.41 88.78
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 84.03 85.49 84.62 84.11 89.00 89.08 85.88 84.64 85.14 85.31 91.59 89.31 86.01 86.88 87.95 88.05 87.15 87.36 88.27 87.60 89.02 89.00 89.47 90.10 90.79
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.63 84.66 84.54 83.76 86.59 85.53 86.50 86.99 87.35 88.42 87.92 90.59 88.28 86.22 87.39 88.12 87.10 88.33 86.72 93.02 89.38 90.40 87.25 90.93 90.07
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 87.64 61.30 87.87 60.32 90.47 91.06 89.66 59.74 90.93 59.59 92.06 89.31 87.80 58.86 59.21 89.18 58.78 91.43 89.09 91.96 58.79 58.44 59.20 59.65 57.92
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 89.68 61.30 88.66 60.53 89.72 93.22 89.91 60.42 88.25 90.94 58.35 93.18 87.08 91.68 90.29 91.42 59.61 93.22 89.16 92.17 55.85 57.59 92.46 57.11 57.41
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 87.64 59.90 87.64 61.82 89.67 89.14 88.40 89.41 89.93 89.90 91.80 89.03 91.65 87.67 43.72 86.68 90.92 90.42 57.16 89.15 88.62 56.83 58.84 59.35 60.03
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 90.17 90.92 59.26 90.49 88.41 92.18 89.90 90.13 90.71 89.42 92.47 56.56 87.56 60.02 58.79 90.37 59.55 92.83 57.08 58.76 58.85 56.76 56.88 58.04 56.86
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 88.23 88.67 88.41 90.09 89.81 89.27 90.29 59.27 88.25 89.66 89.78 58.16 90.36 90.97 60.61 90.91 59.27 91.15 92.44 90.37 89.38 57.79 58.88 57.38 58.39
Size of the All data:  (100, 28)
Size of the Sig data:  (46, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
17 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 91.42 89.71 93.65 87.12 90.62 91.85 94.29 90.54 89.90 91.12 92.60 88.77 89.97 90.32 59.15 89.51 59.15 91.24 85.68 87.29 91.10 90.42 90.18 91.86 59.31
8 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 92.35 90.96 94.04 89.83 88.15 91.19 93.21 91.17 93.41 89.31 93.20 87.84 94.32 92.77 70.79 94.44 91.10 90.53 90.15 91.43 83.08 92.39 93.26 91.48 90.78
1 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 90.95 86.68 93.58 67.88 93.04 92.25 93.49 91.38 90.20 94.45 92.70 89.92 91.61 92.15 89.66 92.60 95.88 94.86 94.65 91.40 93.40 93.46 93.06 59.93 91.23
14 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 91.80 92.49 93.06 92.59 94.92 93.93 93.16 93.44 89.70 93.43 91.94 91.10 90.16 91.81 90.04 93.73 92.41 91.51 93.67 91.80 92.76 86.25 92.01 91.46 91.58
2 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 94.20 93.47 93.99 92.52 94.83 95.10 91.75 93.41 95.11 94.35 92.90 91.74 89.98 89.75 93.46 93.76 95.16 92.90 93.48 93.37 91.10 92.29 93.46 91.12 88.63
37 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 58.84 61.05 61.47 59.25 61.92 59.43 58.95 61.83 58.57 61.42 59.62 61.93 59.42 59.83 61.41 59.28 90.43 58.21 58.16 58.63 59.16 62.87 62.67 62.50 61.72
44 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 59.49 61.87 59.93 61.72 61.94 60.61 59.14 62.14 58.97 61.99 59.25 59.89 59.67 59.52 60.57 59.87 62.28 59.01 59.48 61.90 62.32 62.55 50.39 61.94 62.03
36 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 59.18 62.08 59.37 59.20 59.79 59.92 59.14 61.71 62.06 59.41 59.90 59.58 59.99 58.74 61.76 59.68 61.56 59.33 62.64 59.88 62.45 62.55 61.60 62.46 61.76
29 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 58.99 59.72 59.33 61.59 59.20 59.78 59.23 62.15 58.61 61.98 60.84 59.90 59.14 61.95 62.06 59.43 59.84 58.74 51.80 59.95 61.56 62.22 61.65 62.39 62.03
11 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.95 91.59 94.03 92.10 93.67 91.16 93.56 92.03 92.80 94.10 91.70 93.22 90.51 93.23 85.61 93.76 91.67 94.15 91.63 93.87 94.04 92.72 91.05 59.53 92.98
4 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 90.08 89.78 95.16 91.27 94.40 92.24 93.73 59.22 89.69 94.23 93.56 90.63 95.43 92.18 93.14 93.92 91.36 92.30 92.24 94.37 93.13 92.95 91.65 60.70 92.84
10 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 94.85 93.37 94.58 93.60 88.49 92.41 95.60 91.14 93.18 93.32 93.02 91.45 94.45 94.91 93.96 90.87 90.43 93.69 92.31 89.46 90.15 58.98 93.92 92.34 91.91
34 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 59.79 61.28 58.64 61.99 61.93 59.98 58.63 59.17 58.51 59.12 59.33 62.32 59.43 59.56 61.65 59.57 60.29 58.74 59.80 59.43 62.48 61.56 62.34 62.99 61.94
28 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 59.99 61.99 61.65 61.93 59.41 59.71 59.19 59.84 58.19 58.54 60.06 62.70 59.14 59.61 61.48 59.13 62.56 59.64 60.15 58.56 60.63 61.83 59.88 62.78 62.10
38 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 59.39 59.15 59.57 62.39 60.27 60.02 59.38 62.32 59.42 59.56 62.97 59.32 59.63 60.72 61.93 59.58 61.70 59.52 61.93 50.96 62.34 62.57 87.88 62.15 62.13
26 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 59.62 61.93 50.73 61.93 59.34 59.86 59.41 59.86 52.41 59.37 59.68 59.80 59.67 58.37 61.11 60.27 58.97 61.45 59.96 61.99 61.22 61.92 59.43 62.46 61.81
20 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 59.47 49.98 58.86 60.19 60.23 59.78 57.95 51.19 59.11 59.57 60.38 60.49 52.74 60.08 59.35 58.63 58.51 59.69 59.90 59.87 62.55 60.78 59.69 61.83 62.45
0 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 94.19 90.90 90.84 91.66 95.26 91.57 94.89 93.40 94.35 93.48 92.71 92.47 92.06 94.79 93.24 95.37 90.54 91.11 92.75 92.35 58.52 92.53 91.17 92.05 93.54
15 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 94.28 90.49 93.53 91.49 93.49 92.08 94.27 93.27 92.27 91.95 93.36 92.92 91.38 94.82 87.56 93.06 93.74 93.11 92.68 94.12 92.64 95.06 91.86 52.49 59.55
16 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 95.06 89.72 91.66 93.80 92.61 91.53 93.76 93.01 92.28 92.95 91.69 93.94 94.12 91.35 94.42 93.33 96.19 92.82 92.79 92.19 93.98 93.16 94.17 92.58 68.98
35 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 59.56 50.77 59.58 61.70 61.99 59.85 59.30 62.70 59.29 61.99 59.71 59.47 59.91 58.97 61.07 59.24 48.63 58.33 59.95 59.65 61.43 62.59 60.43 62.79 61.67
30 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 58.39 59.87 59.27 62.34 58.04 59.76 59.26 60.81 59.23 59.02 60.27 61.99 59.34 58.97 59.44 88.21 61.26 59.34 62.44 59.67 62.48 61.76 61.64 62.04 62.83
25 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 59.23 60.81 59.32 62.32 59.43 59.79 59.22 61.54 50.51 58.64 59.95 61.59 59.54 60.61 59.34 59.42 59.30 89.36 59.52 58.53 60.79 63.09 60.02 63.04 63.27
7 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.05 91.38 94.72 93.19 90.28 93.68 93.75 92.66 92.64 94.20 93.23 94.81 94.08 92.23 91.67 92.96 92.14 94.84 94.51 92.27 92.53 91.61 89.13 61.90 87.80
9 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.36 92.41 92.03 90.34 90.39 93.05 94.18 93.77 92.96 93.39 91.64 93.58 92.92 95.46 93.51 91.97 90.96 92.04 92.89 93.30 91.80 95.07 88.88 93.09 92.51
41 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 60.04 61.75 59.80 59.81 61.99 50.27 59.95 61.77 59.55 59.34 60.77 88.17 59.69 62.41 62.64 90.69 60.96 58.88 60.43 62.26 62.46 63.04 59.57 62.34 62.61
31 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 93.25 62.32 62.64 61.79 59.80 59.18 59.69 60.13 59.70 59.57 61.20 61.07 59.33 59.91 60.90 59.71 61.32 59.57 60.22 60.32 62.55 63.11 62.72 61.64 62.26
45 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 59.14 60.32 59.82 62.64 59.19 60.37 59.53 61.76 51.03 59.61 60.67 61.26 60.80 60.72 62.64 59.23 60.95 59.56 62.97 62.32 62.72 61.39 62.17 62.80 61.33
39 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.52 59.79 59.14 59.95 59.80 60.87 52.25 62.97 59.37 62.03 62.97 62.39 60.97 61.21 62.32 59.61 61.70 59.71 59.80 59.62 60.25 62.75 62.48 62.72 62.03
6 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 92.67 94.38 93.26 91.17 94.49 92.91 91.39 89.88 93.59 93.35 94.72 93.54 94.80 88.14 93.49 91.57 91.68 93.77 91.13 92.37 61.03 93.21 94.43 93.94 89.94
13 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 95.16 92.56 88.22 90.20 91.91 92.76 94.47 94.19 92.58 92.09 92.14 91.85 92.77 94.70 51.18 94.56 94.38 92.64 92.37 93.06 61.67 92.36 91.43 94.84 92.74
5 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.00 93.69 95.54 91.07 89.48 92.31 93.35 92.64 92.31 93.84 89.18 94.39 90.38 92.86 91.41 93.57 90.27 89.99 92.21 92.87 92.24 92.54 61.11 92.86 70.78
33 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 59.91 62.06 59.85 60.22 59.62 59.19 92.87 60.03 60.08 90.63 50.51 61.71 59.62 59.21 62.06 60.37 59.90 59.58 60.27 61.99 62.25 62.70 62.39 61.78 62.75
40 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 59.45 59.70 61.74 59.72 59.21 60.33 61.20 62.41 59.81 59.50 51.47 62.72 60.34 58.92 61.87 59.85 61.61 59.98 60.22 62.32 61.55 62.45 62.79 62.50 61.81
27 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.42 52.56 59.93 62.39 59.46 59.33 60.53 50.74 60.65 59.57 62.97 61.93 51.36 60.72 61.76 50.40 61.66 60.86 60.83 59.53 62.36 62.57 60.44 63.09 62.44
32 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 60.43 59.65 59.41 61.99 59.81 59.45 60.40 62.90 59.46 61.76 60.73 62.32 60.60 59.86 52.81 59.54 61.64 59.61 60.77 60.77 62.48 62.39 62.60 62.32 62.97
22 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 60.32 61.01 59.62 59.48 59.80 60.77 59.48 62.26 60.77 60.89 49.99 60.00 59.57 60.03 61.45 91.04 59.71 60.81 60.43 61.94 62.91 62.03 62.71 62.68 51.89
18 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.36 92.56 94.32 91.82 95.50 90.05 92.67 93.12 94.56 93.18 92.63 92.37 94.68 94.64 88.37 92.70 48.12 93.22 89.68 91.30 91.74 92.36 92.46 56.53 92.61
19 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.33 96.37 91.19 93.37 95.37 92.15 95.78 93.31 93.31 93.08 93.84 92.27 91.78 87.67 48.12 94.38 48.12 90.83 92.11 92.25 93.78 93.33 93.26 91.47 91.64
12 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 90.71 94.11 90.14 92.09 94.61 92.87 93.48 91.67 94.93 94.47 92.71 92.29 95.04 92.02 94.50 94.52 93.27 94.86 92.32 92.34 93.98 94.02 94.16 92.60 90.30
3 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 92.55 88.17 93.56 87.90 93.08 93.26 92.77 93.30 94.07 93.37 91.79 93.07 91.98 95.89 94.92 93.92 92.10 92.87 93.10 91.17 93.96 92.72 92.46 90.35 93.19
42 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 60.37 61.99 60.27 61.93 59.31 59.63 59.95 62.88 59.57 61.76 60.22 60.94 61.31 61.03 61.50 51.78 61.61 59.56 61.13 59.16 61.45 62.35 62.26 62.32 62.44
23 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 59.86 63.04 59.77 61.99 59.31 59.76 60.29 62.26 91.13 59.79 62.64 60.11 50.28 59.85 59.95 59.86 62.09 59.23 51.59 59.99 62.55 62.34 59.05 62.43 62.30
24 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 59.85 62.64 60.19 62.06 59.95 60.77 59.53 59.72 59.83 60.09 59.90 61.20 59.62 89.99 48.12 51.38 59.66 59.65 62.64 60.67 60.26 63.04 62.79 62.77 61.68
43 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 59.56 59.80 62.32 59.50 60.12 60.01 60.08 60.50 59.69 59.86 59.71 62.84 60.73 61.53 61.70 60.53 61.24 59.58 62.97 62.06 62.66 63.04 62.57 62.03 62.53
21 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 59.95 60.17 59.47 59.36 59.57 61.30 60.00 61.52 60.83 60.03 61.07 62.41 60.29 60.08 61.48 60.33 61.01 60.27 59.80 88.26 60.26 63.02 62.39 62.36 61.87
Size of the test data:  (46, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

key_values = ['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']
print('Are the keys of the valid and test dfs same?: ',dt_mw[key_values].equals(test_data_mw1[key_values]))
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.77 -6.31 -30.32 -29.70 -29.84 -32.42 -30.44 -35.67 -31.40 -31.82 -31.29 -30.91 -33.22 -31.61 -32.40 -33.10 -33.82 -31.45 -32.02 -33.43 5.21 0.58 -31.22 2.30 3.84 21
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.56 -5.71 -30.53 -0.48 -0.71 -30.58 -30.16 3.14 -32.05 0.92 -32.26 -33.23 -29.85 -31.07 -0.79 -31.95 -6.68 -32.70 -31.48 -32.70 1.54 4.30 -29.49 3.72 2.84 19
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.28 -28.50 -28.94 -30.73 -30.24 -27.97 -30.29 2.25 -27.42 -29.63 -28.71 4.25 -30.07 -30.89 0.87 -30.58 1.74 -30.88 -32.64 -2.11 -29.12 5.23 3.51 4.98 3.48 17
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.07 -0.62 -29.80 -31.24 -31.13 -29.85 -29.44 1.82 -28.59 -28.15 -39.75 -31.42 -32.10 -30.14 2.41 3.91 -32.46 -27.57 -30.99 4.17 6.46 4.29 4.87 5.82 -35.61 17
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.72 -1.06 -30.90 1.03 -29.54 -32.25 -32.15 1.76 -6.01 -32.07 -32.49 4.01 -30.97 1.69 -30.11 -32.51 -32.43 5.46 -32.95 -31.63 -27.93 7.19 -29.63 5.07 7.02 17
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.12 0.39 -5.29 1.17 -30.89 -31.69 -31.42 -30.07 -35.62 -31.11 -33.26 -32.41 -32.50 -31.76 0.41 -29.89 -32.26 -0.06 -31.72 3.00 0.85 2.54 -31.88 3.14 2.17 17
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.25 0.75 -29.07 -29.60 -28.76 -30.00 -28.30 -0.24 -0.31 -32.03 -31.24 -30.87 -27.66 -32.72 1.23 -30.74 0.13 -31.85 4.29 -31.41 4.03 4.01 -0.31 0.91 2.09 17
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.04 -34.53 -29.98 1.43 -29.76 -32.64 -25.30 -36.64 -29.70 -31.64 4.45 1.68 -35.91 -28.38 1.45 -38.32 1.96 -27.81 -29.80 -31.64 3.79 4.91 -27.61 5.39 2.58 16
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.14 0.59 -30.47 -0.32 0.64 -32.41 -30.86 -31.37 -31.50 -31.83 -32.57 2.89 -31.12 -32.16 1.31 -30.01 -0.34 -32.13 -31.26 -31.90 5.21 1.51 2.50 4.30 3.46 16
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.06 0.34 -0.07 0.88 -29.79 -32.72 -30.09 -31.14 -32.72 -31.68 -31.99 3.82 -32.82 -31.00 3.03 -33.84 3.72 -30.07 -31.52 -33.90 2.59 2.88 -30.37 4.71 4.49 16
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.79 2.74 -27.45 0.24 -29.72 -28.37 -28.87 -29.69 -30.10 -29.81 -31.90 -27.83 -32.03 2.32 4.40 -35.30 -31.26 -30.77 5.48 -28.48 -28.36 6.21 3.95 3.42 1.65 16
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -26.96 -30.04 -29.31 0.92 -30.38 -32.77 -26.45 3.65 -31.23 2.21 -29.52 4.27 -29.75 -32.06 -35.96 -31.73 1.34 -30.81 -29.85 -29.86 5.42 4.92 4.93 2.65 5.86 15
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.48 -30.10 -29.46 2.58 -31.99 -31.88 -31.98 1.33 -32.13 3.18 -29.42 -32.28 -31.82 2.69 1.27 -32.12 -30.98 -33.36 -37.26 -32.98 0.80 4.24 2.17 4.57 3.88 15
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.18 -0.21 -27.10 0.26 0.68 -30.01 -29.44 1.47 -31.57 0.39 -32.21 -32.32 -31.25 -31.95 -2.45 -31.27 1.55 -32.15 -33.49 3.28 2.98 3.48 -6.55 1.89 2.77 15
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.82 1.74 -28.89 1.46 -30.41 -33.46 -29.62 1.84 2.88 -31.15 4.29 -33.07 -36.80 -31.83 -30.34 -31.56 2.48 -33.99 -37.57 -32.18 6.70 4.75 -33.41 5.32 4.89 15
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.75 -28.98 -1.73 -28.96 -29.99 -30.57 -24.59 3.26 -29.60 -31.21 -39.93 6.39 -29.27 -31.79 1.60 -31.34 1.95 -29.68 -30.44 3.15 5.32 6.11 5.51 6.12 2.61 15
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.75 -0.16 -27.83 -28.93 -29.98 -33.52 6.06 -29.38 -30.33 8.06 -5.73 2.50 -31.81 -32.98 2.28 -30.54 -31.02 -32.14 -32.42 3.47 6.60 6.00 4.96 2.53 5.67 15
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.91 -29.38 -29.01 -29.46 -29.52 -29.99 -33.76 4.18 -31.17 2.83 6.10 2.96 -27.30 -0.11 2.84 -32.57 2.19 -30.73 -33.67 -32.85 -29.52 4.57 4.92 5.99 3.64 15
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.56 1.15 2.84 1.53 -28.37 -32.79 -29.72 -31.02 -32.25 -29.85 -27.59 -28.73 -31.12 -31.01 1.60 -31.72 3.22 -31.10 -30.97 -30.60 4.49 7.87 4.20 2.69 3.03 14
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.00 -30.78 -29.58 1.15 -30.59 -32.46 -30.35 1.13 -32.31 -32.47 -30.78 3.20 -31.16 -32.48 -33.21 5.26 2.11 -31.28 3.51 -31.52 5.59 3.62 2.24 2.04 5.26 14
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.27 0.69 -27.60 1.61 -31.16 -31.43 -29.71 3.14 -31.36 2.17 -31.84 -28.37 -26.49 2.17 2.29 -37.40 2.83 -31.87 -27.96 -32.80 2.66 3.91 3.06 2.67 4.52 13
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.52 -30.51 -28.35 1.73 -29.08 -29.68 -30.44 1.60 -31.92 -32.16 6.19 -34.40 -30.36 1.17 1.88 -31.63 0.83 -31.92 1.68 -37.74 4.21 4.93 4.80 1.65 3.78 13
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.59 1.06 0.61 -31.06 1.41 -32.54 -30.52 1.34 -30.61 1.26 -32.85 4.16 -33.22 -31.27 1.08 -33.80 6.47 -32.58 -33.40 -32.32 -32.38 4.17 5.04 4.27 2.32 13
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.61 -31.12 3.06 -30.99 -28.29 -32.17 -29.82 -29.63 -31.02 -29.56 -32.76 6.28 -26.83 1.51 2.91 -29.84 1.69 -33.25 5.89 3.30 3.81 6.28 5.69 3.99 5.67 13
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -31.56 -29.33 -28.58 2.22 -29.77 -31.27 -30.42 1.85 -36.58 -30.83 -29.46 -27.03 -27.24 1.08 2.28 -32.99 2.30 -31.12 6.46 3.32 6.57 2.35 4.89 6.63 2.05 13
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.10 0.48 -28.37 -30.12 0.94 -37.05 -30.21 1.13 -32.65 -29.62 -28.84 6.82 -30.47 1.55 3.69 4.98 2.96 -33.83 -29.71 5.04 5.38 6.43 -30.29 5.04 6.73 12
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 23.92 20.43 5.46 -1.60 1.88 6.28 10.38 -0.25 -0.55 0.80 3.72 23.76 1.99 0.01 -25.31 5.57 -28.39 4.81 2.75 0.30 0.36 2.22 2.03 2.72 -28.92 6
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.70 7.77 10.91 6.17 6.51 4.02 8.99 5.11 5.67 6.06 -1.50 6.54 0.64 6.35 2.93 7.69 -0.63 4.91 2.97 3.30 2.12 2.86 -27.47 2.36 -20.54 4
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.01 2.46 9.04 4.72 2.61 1.76 8.17 0.81 8.92 1.91 6.13 -0.72 8.86 3.81 -18.06 6.79 4.03 3.07 2.10 1.15 -6.81 2.15 6.20 2.60 2.05 3
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 1.90 -2.05 9.14 -19.79 4.39 3.78 7.97 5.20 5.03 5.82 4.55 2.94 8.59 4.34 1.59 5.08 8.21 6.59 5.71 2.57 4.93 3.69 4.10 -29.23 1.59 3
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.93 3.26 1.59 2.55 5.34 1.25 10.44 5.06 3.58 5.08 1.15 4.10 5.48 6.54 -38.04 7.79 6.80 3.87 3.55 -0.90 -29.48 3.02 3.88 38.71 2.72 3
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.71 36.23 2.67 5.03 8.74 6.80 8.06 6.64 4.86 6.38 2.52 1.63 3.64 4.41 -0.46 4.16 1.73 3.83 5.78 -0.54 5.27 -0.91 2.12 2.34 3.42 3
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.62 34.88 7.32 4.42 10.61 5.73 10.41 4.40 1.58 7.56 5.48 0.43 3.60 9.33 -3.29 5.15 4.71 2.79 3.74 5.47 4.78 6.60 2.05 -37.42 -30.22 3
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.49 3.69 9.10 5.09 10.20 4.85 9.93 -29.99 2.85 7.76 3.26 4.37 8.88 5.87 4.39 5.06 1.75 5.47 1.48 6.13 3.68 3.63 2.57 -30.33 4.41 2
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.43 5.04 8.65 7.47 11.25 5.64 9.58 5.31 7.40 3.60 5.36 3.45 1.88 2.21 -0.86 6.43 5.00 7.19 2.34 2.05 5.70 2.91 2.24 -31.62 4.62 2
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.92 3.51 9.02 4.14 6.49 7.73 6.27 6.31 6.72 4.95 3.87 2.48 3.70 9.67 7.53 5.80 5.00 4.54 6.38 -1.85 4.58 2.32 5.21 -0.58 3.12 2
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.54 6.98 8.28 5.52 5.65 4.08 8.32 5.85 5.12 5.35 0.88 8.94 5.98 6.86 6.67 3.80 3.47 9.07 5.44 4.59 4.70 3.72 2.16 -33.01 -1.80 2
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.04 7.77 7.83 5.20 10.26 1.44 6.71 4.91 7.37 5.57 4.18 3.72 7.75 6.70 0.07 37.24 4.40 4.95 1.94 2.26 2.82 3.85 3.12 -35.22 3.29 1
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 6.68 8.62 5.52 7.98 5.61 3.79 7.60 7.03 9.79 9.16 1.12 2.98 9.03 5.14 6.55 6.47 6.12 7.50 4.05 4.74 4.96 5.02 4.69 2.50 -0.49 1
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 11.59 7.14 7.66 6.93 1.47 3.45 11.66 3.18 7.50 5.88 6.03 2.62 8.43 6.50 6.52 1.98 3.99 6.58 1.89 2.00 2.39 -30.86 3.28 4.02 3.76 1
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.05 5.80 3.63 5.65 9.00 4.93 7.59 6.72 5.77 7.97 3.43 7.00 3.04 6.33 3.75 7.08 2.09 1.30 2.63 4.22 -31.09 3.63 1.36 2.71 4.34 1
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.62 8.88 7.67 7.03 8.36 7.31 6.24 6.60 7.59 6.56 2.73 0.85 4.94 1.90 8.27 6.96 6.61 6.80 2.37 2.37 4.19 2.22 4.35 1.66 -3.11 1
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.39 3.77 7.45 4.33 6.84 1.25 6.52 4.51 5.53 5.43 7.17 40.43 8.19 4.75 4.54 5.53 10.14 5.95 4.24 2.57 6.32 4.40 5.10 4.61 -22.68 1
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.54 7.81 9.43 3.57 10.15 6.27 4.85 3.98 5.01 8.38 7.19 5.11 7.37 1.25 5.84 5.04 1.33 5.24 0.39 1.00 -33.42 4.96 5.95 5.19 3.06 1
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.50 4.11 5.82 6.22 5.79 7.02 8.76 5.43 6.83 6.66 -0.11 5.11 4.77 9.04 5.64 4.30 4.65 4.27 1.03 5.35 2.76 6.04 1.16 4.75 2.29 1
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.95 10.70 7.35 3.59 8.88 7.32 8.89 5.37 7.47 4.32 6.29 0.58 4.61 0.61 4.40 7.87 4.40 1.76 2.53 1.81 4.91 4.43 4.64 1.06 2.86 0
Are the keys of the valid and test dfs same?:  False

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_6 89.692609 2.358115
mAP_valid_abs_values_18 88.709565 4.639103
mAP_valid_abs_values_13 88.615652 2.176657
mAP_valid_abs_values_16 88.390000 5.496899
mAP_valid_abs_values_9 87.465652 6.439106
mAP_valid_abs_values_7 87.370652 2.312300
mAP_valid_abs_values 86.772609 3.547403
mAP_valid_abs_values_11 86.520652 10.473764
mAP_valid_abs_values_19 85.927174 11.081484
mAP_valid_abs_values_20 84.903043 12.363281
mAP_valid_abs_values_5 84.809348 8.580876
mAP_valid_abs_values_10 84.328261 10.627476
mAP_valid_abs_values_14 83.989130 11.388991
mAP_valid_abs_values_3 83.725435 9.420535
mAP_valid_abs_values_12 80.076957 14.657660
mAP_valid_abs_values_4 78.338043 12.957241
mAP_valid_abs_values_8 77.857391 13.839314
mAP_valid_abs_values_23 77.661739 15.001737
mAP_valid_abs_values_2 76.363043 13.577547
mAP_valid_abs_values_17 75.335435 15.988766
mAP_valid_abs_values_21 74.916957 15.871967
mAP_valid_abs_values_15 74.224565 15.543830
mAP_valid_abs_values_26 72.500652 15.670258
mAP_valid_abs_values_22 71.451304 15.665067
mAP_valid_abs_values_25 71.448696 15.766411


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_16 75.233804 17.072799
mAP_test_abs_values_10 75.211739 16.358892
mAP_test_abs_values_7 75.181304 17.599944
mAP_test_abs_values_12 75.113641 15.163913
mAP_test_abs_values 74.867120 16.746625
mAP_test_abs_values_20 74.587663 15.959395
mAP_test_abs_values_22 74.485652 14.786154
mAP_test_abs_values_5 74.429239 16.417018
mAP_test_abs_values_9 74.390761 17.139923
mAP_test_abs_values_13 74.256793 16.781006
mAP_test_abs_values_3 74.243967 16.495746
mAP_test_abs_values_23 74.239402 15.938178
mAP_test_abs_values_11 74.125924 16.422341
mAP_test_abs_values_14 73.965326 16.245739
mAP_test_abs_values_19 73.934891 16.194125
average_map 73.916957 14.846075
mAP_test_abs_values_8 73.874239 16.010211
mAP_test_abs_values_6 73.796630 16.320558
mAP_test_abs_values_2 73.760924 15.701428
mAP_test_abs_values_18 73.760815 16.664212
mAP_test_abs_values_26 73.225380 14.351369
mAP_test_abs_values_17 72.906630 16.441557
mAP_test_abs_values_21 72.857011 15.007684
mAP_test_abs_values_4 72.852609 15.409223
mAP_test_abs_values_25 71.477554 14.252064
mAP_test_abs_values_15 71.144891 15.373538


Summary using radar plot

Code
def extract_number(text):
    if isinstance(text, str):
        matches = re.findall(r'\d+', text)
        return int(matches[0]) if matches else 1
    return 1

res_valid1['id'] = res_valid1.index.to_series().apply(extract_number)
res_test1['id'] = res_test1.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid1,res_test1])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test1 = res_test1.sort_values(by=['id']).reset_index().query("index !='average_map'")
data_range1 = np.array(list(res_test1['mean']) + list(res_valid1['mean']))
categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test1['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid1['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()

##############


res_valid2['id'] = res_valid2.index.to_series().apply(extract_number)
res_test2['id'] = res_test2.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid2,res_test2])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test2 = res_test2.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res_test2['mean']) + list(res_valid2['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test2['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid2['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()




  • In these experimental results, the thresholding is based on a fixed value of 0. This decision is informed by the fact that the binary-like hash values are symmetrically distributed between -1 and 1.
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
16 372 16 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 83.15 86.55 67.73 85.60 85.90 85.94 82.33 81.63 80.29 87.24 86.82 88.15 88.12 59.43 81.64 82.15 85.18 85.32 78.90 86.64 87.54 79.08 86.53 65.31 85.57
19 372 16 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 82.86 86.57 84.84 71.42 82.57 84.01 82.80 86.21 86.18 84.43 85.14 86.11 84.22 85.29 87.03 87.00 88.05 85.17 88.14 88.24 87.10 85.35 83.32 88.04 86.10
28 372 16 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 81.77 85.53 84.19 89.00 85.19 84.56 84.87 86.17 89.47 83.70 85.83 86.68 86.09 89.30 84.68 82.99 84.55 73.29 88.15 79.98 89.28 87.93 86.33 89.59 87.58
31 372 16 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 83.04 83.53 83.89 86.76 83.84 83.60 83.96 80.74 84.88 86.16 88.51 88.70 84.78 87.61 88.08 82.76 43.72 86.56 88.95 84.07 84.59 86.17 86.12 87.55 85.72
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 84.63 88.42 83.59 84.03 87.12 84.90 84.35 87.86 87.60 85.67 90.03 84.55 87.08 43.72 90.41 86.71 86.93 88.59 86.21 87.19 89.49 88.83 86.98 89.67 86.19
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 85.78 85.10 87.06 85.85 85.75 86.08 87.05 86.50 88.49 85.51 89.27 85.33 88.33 88.43 89.13 88.14 87.98 89.70 90.01 87.96 89.56 88.86 89.76 89.34 88.81
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 85.33 55.49 85.95 86.99 82.75 86.35 83.79 88.80 90.37 83.49 87.88 92.20 87.57 85.43 90.77 87.66 89.01 89.83 88.83 88.65 87.71 88.24 89.60 89.37 89.74
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.39 85.29 84.06 88.72 85.74 90.04 87.22 87.87 86.75 87.21 84.39 52.60 85.86 86.53 89.72 87.72 84.87 86.44 88.54 89.61 87.53 88.71 88.63 87.39 91.23
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 83.67 84.79 86.13 86.58 85.21 88.42 85.83 88.01 87.18 87.61 88.45 88.65 86.86 87.87 88.30 55.25 43.72 88.15 87.41 88.98 88.66 88.26 88.39 91.72 89.32
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 86.13 85.61 83.84 89.78 86.49 84.58 86.42 87.88 84.90 88.74 87.54 91.68 87.17 86.77 43.72 86.43 43.72 89.07 89.56 90.28 88.86 88.90 88.16 90.41 88.53
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 83.43 85.49 84.57 84.11 88.36 88.90 85.41 84.37 85.14 85.20 91.59 89.12 85.76 86.73 87.82 88.02 87.14 87.13 88.27 87.58 88.95 89.00 89.24 90.10 90.54
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.45 84.66 84.54 83.12 86.23 84.71 86.29 86.77 87.14 88.42 87.90 90.15 88.27 85.89 87.39 87.71 87.08 87.84 86.64 92.44 89.17 90.39 86.94 90.74 89.45
208 372 16 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 86.67 87.98 63.59 63.86 62.85 59.20 57.46 61.90 62.14 64.34 58.27 58.80 89.54 60.44 61.16 58.54 61.73 62.59 90.24 59.30 60.42 61.10 59.31 62.18 60.49
211 372 16 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 88.48 61.61 56.27 64.37 43.72 59.39 88.08 59.30 56.11 62.21 58.03 58.90 43.72 58.33 58.84 90.43 61.62 59.41 91.53 57.01 61.19 43.72 58.87 58.82 56.81
220 372 16 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 56.24 63.89 87.93 63.28 64.95 56.29 86.28 62.23 85.18 63.78 61.26 58.82 88.84 62.72 63.11 87.04 57.11 88.61 60.27 56.89 67.23 67.30 55.54 62.53 62.89
223 372 16 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 86.65 55.70 87.44 56.59 63.19 90.64 89.31 61.36 59.41 61.83 91.53 91.85 89.03 59.42 61.08 89.60 61.28 89.44 90.51 56.24 59.78 59.63 60.12 59.77 57.16
272 372 16 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 89.65 60.95 61.79 60.62 61.37 90.47 55.62 56.00 84.71 60.56 92.19 93.81 89.38 92.14 59.70 91.96 59.87 90.09 91.67 58.76 58.89 57.83 90.23 58.01 58.87
275 372 16 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 89.75 59.88 60.05 60.38 90.49 90.23 85.22 91.72 59.53 85.09 89.17 58.76 91.18 59.96 59.59 91.54 54.77 91.43 91.44 92.98 60.29 59.70 58.48 59.14 57.48
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 88.12 56.48 90.11 61.64 62.69 90.30 89.46 59.56 91.30 60.93 91.97 92.55 89.70 90.04 61.86 91.19 55.31 91.03 91.43 92.23 59.09 58.29 89.92 58.82 58.82
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 88.39 90.65 88.41 61.00 88.52 91.99 89.35 59.44 91.54 91.49 90.93 58.79 90.42 91.45 92.63 82.72 58.98 90.62 58.93 91.19 56.88 57.78 59.02 60.00 57.57
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 87.64 61.05 87.87 60.19 90.47 91.06 89.66 59.61 90.93 59.59 92.06 89.31 87.80 58.83 59.21 89.18 58.31 91.43 89.09 91.96 58.79 58.31 59.19 59.65 57.70
339 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 87.41 90.69 86.65 60.40 87.11 92.18 85.83 59.96 90.15 89.16 89.54 58.52 84.51 57.93 60.38 90.66 91.71 90.19 57.70 58.87 58.25 56.58 90.42 56.61 57.64
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 89.66 60.44 88.66 60.41 89.72 93.22 89.91 60.42 87.90 90.94 58.35 93.18 86.83 91.42 89.92 91.42 59.48 92.97 89.16 92.17 55.85 57.59 92.46 54.75 57.24
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 87.64 59.77 87.64 61.82 89.67 89.14 88.40 89.16 89.93 89.90 91.68 89.03 91.65 87.55 43.72 86.68 90.68 90.42 57.16 89.15 88.62 56.83 58.83 59.35 60.03
400 372 16 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 88.53 62.34 56.40 63.43 63.08 56.76 63.24 62.62 62.40 61.88 59.08 59.72 57.32 62.63 43.72 89.15 62.85 61.47 60.94 60.47 61.38 62.71 61.73 62.73 64.98
403 372 16 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 57.01 60.65 55.84 56.06 58.59 57.09 57.50 61.17 56.04 87.87 90.59 56.27 88.86 59.33 60.32 91.02 59.43 59.68 56.63 56.62 62.23 58.94 59.70 43.72 60.31
412 372 16 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 43.72 87.83 62.18 63.60 63.48 55.91 87.76 61.25 56.83 62.98 89.82 59.61 89.04 61.85 60.79 62.26 63.26 62.29 91.35 58.71 61.80 58.17 63.21 58.59 62.80
415 372 16 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 54.68 54.45 57.68 57.89 57.44 89.79 90.47 59.15 88.09 56.75 53.85 55.47 91.73 56.81 59.04 55.10 89.59 91.21 91.44 53.96 54.75 57.66 51.45 58.45 56.97
464 372 16 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 88.70 60.70 55.52 43.72 60.60 55.78 87.67 59.31 90.25 63.19 57.22 91.96 90.42 91.72 59.67 92.09 60.86 59.37 58.80 58.71 57.69 59.94 58.86 58.11 59.08
467 372 16 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 87.78 62.34 88.81 61.42 61.39 90.89 90.45 61.07 60.33 90.44 91.16 59.53 91.17 60.58 60.47 91.68 60.89 90.72 92.34 86.61 58.47 61.03 53.15 61.66 60.90
476 372 16 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 87.87 62.80 89.32 88.85 89.43 56.05 88.28 61.77 55.96 90.74 88.21 59.78 90.91 90.34 60.50 91.20 59.98 88.90 90.94 58.57 57.60 60.88 87.58 58.89 58.43
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 87.95 61.87 89.97 61.10 88.97 91.42 91.37 59.53 56.52 90.71 92.44 57.58 90.43 58.92 89.22 91.93 91.73 83.67 92.46 90.16 88.59 55.64 89.38 57.92 56.12
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 90.17 90.92 59.26 90.49 88.40 92.18 89.90 90.12 90.70 89.42 92.47 56.30 87.56 60.02 58.48 90.37 59.01 92.74 57.08 58.63 58.60 56.73 56.76 57.91 56.86
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 88.02 88.67 88.41 90.09 89.68 89.27 90.24 59.27 88.01 89.41 89.78 58.16 90.36 90.97 60.61 90.91 59.14 90.90 92.44 90.36 89.38 57.78 58.13 57.38 58.39
540 372 16 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 87.16 61.01 88.87 60.54 88.66 56.81 88.89 58.65 87.67 58.21 88.60 56.72 89.51 89.05 60.25 87.41 59.29 90.92 90.28 59.16 54.51 55.90 56.95 57.13 56.86
543 372 16 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 87.90 60.18 61.16 87.78 88.67 90.23 87.34 57.89 59.40 61.42 57.91 92.93 90.65 57.54 59.93 91.68 59.80 91.17 90.15 87.97 58.14 56.79 56.35 58.34 56.38
592 372 16 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 84.08 80.22 85.36 81.60 85.38 84.58 83.15 82.37 83.81 84.73 86.75 85.44 82.44 88.83 84.74 78.76 87.42 81.54 81.29 87.19 83.10 84.63 76.94 82.69 86.07
595 372 16 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 82.84 84.44 83.41 84.70 87.27 80.76 85.20 86.59 82.64 86.92 87.03 85.98 85.08 86.97 87.88 85.51 89.05 87.15 87.76 64.99 86.49 75.68 88.06 88.69 87.54
604 372 16 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 84.55 83.77 86.09 83.06 85.80 83.10 80.14 85.06 84.33 84.92 61.53 85.98 85.33 87.62 88.92 84.67 87.79 86.36 87.53 87.62 86.86 86.20 86.98 87.39 87.30
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 67.25 69.05 87.80 88.19 88.71 85.38 83.67 90.58 90.27 90.32 88.71 64.42 87.92 88.57 84.30 83.58 87.51 85.72 81.95 72.89 90.53 88.11 88.10 89.10 87.69
656 372 16 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 60.04 87.84 85.51 83.37 86.01 86.65 84.90 55.03 84.99 86.32 86.69 86.24 86.32 86.40 88.24 88.15 86.56 87.50 89.52 89.96 88.13 88.68 89.21 90.17 87.88
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.48 86.20 85.22 84.23 82.40 85.49 83.94 86.14 84.96 90.00 85.69 89.30 88.31 90.67 86.05 87.08 86.65 85.99 88.84 91.57 88.34 89.37 88.76 90.95 87.33
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 84.83 83.87 85.88 85.94 84.20 86.71 83.54 88.89 86.68 85.46 90.01 86.19 86.43 86.14 88.75 88.74 89.55 86.60 90.65 87.92 89.38 89.22 88.77 90.98 88.30
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.26 86.21 86.70 86.64 86.79 88.41 83.54 87.94 85.52 87.25 86.95 88.36 86.00 87.76 87.40 88.76 85.35 87.11 89.34 87.46 87.33 89.84 90.51 88.31 88.02
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 84.04 86.42 83.62 87.03 84.32 86.52 86.53 85.36 88.58 84.96 87.46 88.42 86.99 86.31 87.64 86.45 90.35 88.16 90.52 91.09 94.45 87.99 88.48 88.75 86.83
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.04 89.27 86.62 86.82 86.33 91.31 84.03 89.00 88.66 86.85 90.99 87.54 87.29 87.78 89.05 86.66 87.18 88.10 88.82 93.96 91.12 89.24 87.17 55.98 90.02
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 82.65 85.25 84.79 43.72 83.75 87.82 84.32 88.47 84.22 84.95 90.98 87.10 88.02 88.46 85.99 88.04 86.45 86.56 85.51 87.03 88.77 89.08 87.96 89.26 88.93
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 83.55 85.74 84.63 84.88 82.47 88.00 84.12 87.47 86.10 87.44 90.31 87.43 89.65 85.66 88.47 85.50 90.54 84.64 89.04 89.56 90.07 89.50 88.34 90.37 91.10
784 372 16 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 57.80 63.46 63.16 63.27 63.29 60.56 86.29 63.44 57.12 63.12 59.87 55.93 88.33 61.40 63.02 61.16 62.25 61.92 58.82 60.20 64.54 64.07 65.23 62.91 61.72
787 372 16 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 87.93 61.65 62.84 60.88 61.49 90.04 87.75 59.58 90.33 61.62 85.58 59.11 83.15 62.14 62.18 90.16 59.82 62.45 58.77 91.29 61.49 59.55 61.18 61.92 58.89
796 372 16 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 87.42 64.55 56.67 64.57 65.08 89.72 88.11 63.06 88.27 64.64 90.92 58.25 90.87 63.35 61.66 62.47 63.96 89.42 59.31 59.61 65.19 66.58 60.59 62.29 60.11
799 372 16 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 88.60 55.47 59.84 61.14 60.11 91.07 87.74 60.11 58.79 87.55 90.53 55.31 88.65 58.60 57.76 89.94 57.70 56.64 91.91 54.53 55.49 58.48 57.17 59.56 55.73
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 88.80 60.46 88.99 62.31 61.12 92.25 89.45 90.54 90.01 55.67 91.68 59.18 90.55 91.72 60.28 89.32 60.38 90.76 90.93 91.20 56.95 60.00 59.84 58.69 58.10
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 89.05 61.41 61.72 61.05 89.20 92.43 89.23 90.97 90.68 90.06 92.05 58.77 91.68 90.59 58.42 92.73 58.84 89.71 91.67 92.46 58.02 58.82 90.25 57.72 57.60
860 372 16 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 88.90 62.37 87.99 90.64 90.47 90.93 87.63 59.29 89.57 60.25 58.37 58.48 91.92 59.91 60.78 59.76 59.76 60.41 91.02 92.19 58.95 59.97 54.59 59.87 57.05
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 87.15 89.51 87.86 60.59 89.11 89.70 89.77 60.72 91.09 91.72 56.53 93.59 89.17 59.55 60.05 91.21 60.87 91.19 60.25 88.59 58.13 57.64 83.08 60.50 58.19
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.66 62.10 87.68 89.15 89.47 92.36 86.60 89.37 90.15 82.22 56.01 59.21 91.43 91.94 59.78 90.66 90.92 91.72 92.17 58.52 55.65 56.58 57.43 59.02 56.83
915 372 16 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 89.67 60.69 89.19 55.25 88.08 57.39 87.82 89.52 86.32 90.52 89.88 57.22 89.93 58.78 58.55 85.10 91.40 90.02 91.30 58.07 58.16 57.85 57.21 58.07 58.25
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.20 88.68 63.43 88.68 89.20 90.89 85.79 58.90 89.17 90.71 91.40 56.33 89.36 90.71 60.14 91.19 59.64 89.66 90.66 59.17 56.23 56.00 57.16 56.15 58.95
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 88.46 87.09 89.66 60.96 89.22 91.97 85.83 87.38 90.35 91.21 58.52 60.25 87.04 89.10 60.31 88.72 59.70 88.67 90.39 91.17 58.57 57.66 88.05 57.70 59.64
976 372 16 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 64.19 64.25 62.22 63.34 62.41 89.37 64.64 63.09 58.07 64.32 57.64 59.65 60.04 59.42 62.28 58.46 58.69 64.48 57.33 43.72 65.85 66.05 57.41 63.48 66.01
979 372 16 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 62.60 61.93 87.08 60.63 63.52 90.94 56.10 59.82 56.79 62.36 91.93 55.98 89.19 60.40 61.00 91.38 61.82 59.26 91.14 55.69 60.80 61.43 62.16 59.84 58.27
988 372 16 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 56.63 63.28 62.66 63.29 62.46 89.32 88.45 62.17 61.09 62.96 90.19 59.02 87.63 61.79 64.04 56.78 89.07 91.77 89.87 58.42 61.66 65.03 63.89 60.93 61.96
991 372 16 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 86.34 61.44 61.39 63.30 59.70 91.40 90.39 61.41 62.86 62.05 57.49 91.09 88.18 57.91 61.65 60.25 61.01 56.99 90.28 54.75 60.40 61.12 58.79 60.37 59.72
1040 372 16 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 88.89 61.17 61.18 61.33 62.57 59.03 89.46 60.20 62.91 92.13 91.40 58.54 89.80 91.72 60.77 92.84 61.25 92.10 59.04 56.06 60.51 58.09 56.87 58.34 59.83
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 88.74 61.30 56.02 60.76 90.23 91.55 90.83 89.82 87.79 90.48 92.69 92.21 92.17 90.13 60.65 90.16 91.23 60.76 91.68 58.62 60.26 59.37 91.31 59.32 59.55
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 89.22 56.29 89.10 89.55 89.98 92.03 88.29 86.85 90.51 91.39 91.67 91.15 85.73 91.43 56.79 91.73 92.20 91.14 91.67 93.30 57.33 59.70 89.95 59.53 58.52
1055 372 16 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 89.75 88.67 60.58 87.11 60.68 91.80 89.75 43.72 60.86 91.45 59.19 59.37 90.27 59.40 61.51 91.80 61.35 92.22 89.20 59.16 57.07 58.30 53.28 59.32 57.96
1104 372 16 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 88.94 89.41 88.09 60.53 89.18 58.62 90.67 58.39 90.22 90.21 56.03 55.53 90.40 91.95 58.85 86.17 58.86 90.99 58.60 56.45 57.40 58.71 58.16 58.58 58.89
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 87.39 89.69 88.72 61.07 89.93 92.22 86.84 59.25 90.46 59.42 90.13 58.04 90.35 91.92 88.77 91.27 60.30 90.42 90.62 90.63 57.06 57.47 57.67 59.67 57.11
1116 372 16 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 88.17 61.95 89.02 60.16 90.69 90.38 89.91 60.50 58.85 58.96 89.03 57.12 91.80 58.10 59.08 88.90 59.93 56.06 89.62 58.76 57.73 56.81 57.31 56.93 56.57
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 87.26 61.63 89.40 90.71 90.93 90.38 88.92 60.44 89.36 88.89 89.74 91.42 91.67 90.17 59.04 86.90 92.17 88.38 90.63 57.64 56.45 57.74 57.84 56.86 87.26
1168 372 16 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 43.72 86.56 82.78 81.68 68.74 86.34 61.11 87.07 87.71 84.40 82.38 82.05 81.26 63.91 82.83 69.15 88.41 86.18 61.20 85.54 87.29 87.00 79.27 85.87 77.39
1171 372 16 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 82.90 82.44 84.01 79.45 83.91 88.70 84.51 83.88 83.37 88.11 85.76 87.61 86.01 83.45 83.75 86.35 85.57 85.18 90.24 86.68 62.99 61.89 85.35 85.05 87.22
1180 372 16 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 83.16 63.55 83.52 87.32 63.13 88.14 84.58 84.08 85.55 83.82 87.90 90.75 81.58 59.82 62.04 86.25 85.98 84.67 88.69 88.70 88.30 87.71 87.13 82.29 81.74
1183 372 16 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 68.40 82.34 82.16 85.50 83.07 83.79 82.39 85.47 83.02 85.78 85.08 86.11 86.38 84.11 87.14 86.09 87.26 85.08 84.01 87.60 86.39 85.59 87.16 83.17 89.30
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 83.53 88.44 84.88 85.08 85.08 89.43 84.85 90.33 84.04 87.40 86.57 87.65 85.39 88.88 88.49 87.10 87.04 87.07 88.05 90.21 89.57 89.90 86.93 88.73 88.68
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.08 88.34 83.96 87.54 88.65 88.35 85.47 85.72 84.54 88.33 87.71 86.85 82.69 87.69 88.06 86.95 87.56 88.23 87.94 88.60 88.42 89.57 88.92 88.46 89.61
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 86.99 56.21 89.61 87.22 85.27 86.52 84.44 86.52 84.84 87.05 89.35 88.93 86.18 86.93 90.46 88.28 90.32 87.66 87.77 92.33 87.06 87.15 89.89 89.03 87.86
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 84.47 83.01 85.60 85.18 85.28 87.60 85.33 86.50 87.33 87.77 89.77 90.62 84.97 87.59 85.17 86.55 88.49 85.67 90.47 91.00 86.41 90.04 88.63 89.31 91.02
1296 372 16 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 83.64 86.70 86.16 86.01 83.74 84.24 83.45 83.75 86.29 84.99 90.09 87.13 85.99 87.26 87.12 84.36 88.75 85.88 91.90 88.39 89.80 87.01 89.01 88.75 86.52
1299 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 83.54 87.87 85.84 87.11 84.48 89.90 87.09 83.97 85.00 87.07 87.90 88.09 85.57 87.65 85.51 85.62 86.40 85.91 88.11 87.06 87.29 87.76 87.12 92.64 87.12
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.38 84.40 86.42 87.16 83.94 89.47 85.43 86.50 87.49 88.84 92.23 85.77 87.70 84.63 84.99 88.64 88.38 85.77 88.99 87.56 87.51 87.63 86.90 94.54 89.58
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.86 88.25 85.90 83.87 84.58 85.85 85.17 88.22 85.54 86.28 91.55 88.28 88.10 85.41 86.97 87.23 86.29 87.53 91.86 87.80 89.01 89.03 87.46 88.34 90.09
1360 372 16 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 65.58 58.26 63.46 62.16 66.03 61.05 57.26 62.22 63.11 56.73 58.81 59.38 56.50 60.51 61.80 89.82 64.48 61.51 59.32 61.35 61.24 64.88 60.92 62.68 60.62
1363 372 16 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 86.64 63.64 65.93 62.95 64.53 61.69 56.73 64.68 63.77 66.23 91.91 59.93 88.64 57.57 61.05 89.95 61.53 62.59 59.80 60.25 61.85 62.90 61.99 62.19 62.29
1372 372 16 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 57.62 65.66 64.73 67.80 65.03 62.65 87.39 65.15 87.94 64.51 89.76 62.30 65.86 64.76 64.38 64.11 64.38 89.94 88.68 62.78 63.23 62.34 63.13 62.31 63.40
1375 372 16 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 56.73 61.81 63.26 63.38 61.45 58.20 86.69 60.27 60.53 62.54 56.65 59.07 89.38 89.17 59.90 60.82 61.69 63.73 58.32 55.22 61.92 65.23 59.44 59.26 58.35
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 89.43 59.37 60.86 90.31 60.29 91.97 89.47 60.36 89.05 59.76 92.47 57.77 92.39 91.04 60.33 92.93 83.96 90.55 91.55 90.95 91.35 57.92 57.50 58.23 59.09
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 88.66 62.08 86.90 61.21 61.26 90.62 88.46 60.64 90.54 61.59 91.46 91.96 90.92 91.47 62.54 91.10 60.73 91.16 92.97 58.62 59.00 59.07 56.94 59.82 59.26
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 88.43 61.33 88.44 88.77 88.55 89.92 87.41 61.70 62.12 91.44 91.11 90.45 87.65 91.46 60.53 89.66 61.29 91.17 58.10 91.29 58.26 57.54 61.57 61.55 59.67
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 88.21 89.50 88.75 59.01 91.13 91.66 91.21 60.61 90.19 58.20 89.71 92.18 90.96 59.26 60.79 91.55 90.78 91.69 89.00 92.93 60.76 57.98 59.35 57.82 57.90
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 89.14 61.27 88.17 89.93 61.05 87.32 90.16 60.27 91.91 88.92 89.61 81.34 89.91 60.86 58.94 85.71 57.72 92.71 89.90 57.22 57.08 56.61 89.86 57.30 55.88
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 84.26 61.17 59.80 60.26 88.17 91.72 89.41 90.90 91.95 89.42 88.79 89.80 90.45 90.92 59.30 91.43 58.08 90.67 91.19 90.92 58.06 54.86 58.52 58.95 59.23
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 90.54 89.65 88.40 60.17 88.71 91.64 89.95 59.78 87.36 90.44 90.13 88.29 87.89 59.52 59.36 92.22 58.65 90.68 56.51 59.00 55.90 59.04 57.28 56.17 59.28
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 89.43 89.17 88.15 89.16 89.32 90.86 85.88 58.54 90.37 59.20 56.75 59.20 88.27 61.32 59.48 92.18 59.51 90.31 93.47 92.35 89.52 58.12 57.56 56.73 58.39
1552 372 16 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 86.07 61.52 63.32 62.94 61.64 57.08 88.35 60.37 63.45 57.01 55.30 55.59 89.58 57.50 88.09 49.75 59.44 61.29 58.14 57.81 58.31 62.57 61.24 53.44 59.37
1555 372 16 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 87.84 64.67 87.41 62.95 61.72 60.18 86.54 62.31 88.40 62.24 91.32 90.85 90.50 59.14 60.14 57.25 88.47 89.08 92.25 58.25 59.67 59.51 53.32 59.97 61.04
1564 372 16 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 56.36 57.80 86.24 86.09 60.49 91.16 88.36 53.19 57.73 89.32 90.32 90.66 89.00 57.70 55.04 91.16 58.54 56.06 92.20 93.10 52.23 57.19 57.32 57.00 56.02
1567 372 16 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 87.90 60.15 62.06 88.05 61.51 88.26 87.44 60.39 62.48 56.69 90.36 54.66 91.42 60.59 62.04 58.14 59.96 60.43 58.37 91.61 60.21 57.99 59.33 56.67 59.48


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
16 372 16 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 89.17 53.79 91.55 93.05 90.65 92.51 90.87 88.72 92.76 54.02 90.24 80.28 90.89 91.06 92.20 89.63 90.72 88.56 83.79 84.41 60.96 86.42 62.30 88.38 93.90
19 372 16 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 94.06 50.70 90.25 80.07 84.43 91.49 93.12 64.15 90.43 92.96 95.24 91.28 92.38 91.85 66.91 92.09 60.25 94.16 92.23 89.11 91.47 57.08 61.26 91.58 89.16
28 372 16 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 91.30 90.74 92.72 61.08 93.34 92.90 53.94 92.45 89.37 82.76 94.72 89.36 91.72 90.53 81.94 87.87 89.35 91.35 90.79 88.35 93.68 92.18 53.79 92.31 91.59
31 372 16 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 93.27 85.60 90.88 52.35 86.17 91.73 93.31 91.27 92.84 92.68 89.67 91.14 91.28 93.30 92.26 92.65 48.12 93.40 90.74 88.92 89.07 91.17 92.01 91.71 93.39
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 89.84 95.59 89.30 92.87 93.64 91.45 93.72 94.63 96.05 95.10 93.32 85.38 93.42 48.12 58.32 78.79 94.49 91.95 93.05 92.38 60.28 92.39 93.12 92.61 91.61
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 94.39 90.90 90.83 91.65 95.27 92.45 94.89 93.57 94.36 93.48 92.70 92.33 92.09 94.71 93.37 95.36 90.57 91.30 92.74 92.52 58.52 92.53 91.34 92.05 93.06
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 93.84 90.64 93.37 91.47 93.39 92.08 94.27 93.29 94.14 91.98 93.36 92.09 91.38 94.82 87.58 93.06 93.73 92.79 92.79 94.12 92.66 95.30 91.86 52.60 59.48
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 95.19 89.90 91.66 93.81 92.61 91.11 93.92 92.79 92.28 92.95 91.71 93.93 94.13 91.67 94.56 93.28 96.33 93.17 92.52 92.19 93.98 93.16 93.88 92.57 68.90
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.08 92.56 95.00 91.98 95.50 89.95 92.75 93.10 94.56 93.18 92.63 92.37 94.71 94.65 88.54 92.71 48.12 93.22 89.43 91.09 91.74 92.48 92.68 56.57 92.61
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.33 96.36 91.19 93.37 95.37 92.15 95.07 93.06 93.12 93.08 93.84 92.27 91.78 86.90 48.12 95.65 48.12 91.03 92.12 92.25 93.78 93.49 92.86 91.47 92.20
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 91.04 94.11 90.14 92.09 94.27 93.11 93.46 91.67 95.06 94.48 92.71 92.29 94.73 92.03 94.63 94.35 93.27 94.86 92.34 92.36 93.98 94.02 94.16 92.60 90.30
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 92.42 88.17 93.81 88.32 93.18 93.06 92.77 93.30 94.09 93.37 91.78 92.68 91.98 95.89 94.92 93.97 92.23 93.10 93.33 91.20 93.22 92.72 92.72 90.34 93.27
208 372 16 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 58.41 59.22 60.50 61.74 62.06 59.74 49.38 60.53 60.71 60.21 59.46 60.54 59.11 59.87 61.42 49.58 59.66 59.76 47.91 59.97 62.93 61.82 63.18 61.35 61.92
211 372 16 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 58.00 60.91 50.36 61.08 48.12 60.33 59.07 60.81 48.91 59.60 60.76 60.69 48.12 59.02 59.90 57.97 60.24 59.32 58.52 60.04 60.69 48.12 61.71 62.89 61.72
220 372 16 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 50.38 61.18 59.53 61.54 61.92 49.64 58.89 62.02 58.50 61.30 61.65 62.34 58.87 61.04 60.28 59.91 48.56 59.30 61.10 50.39 60.60 60.17 51.60 62.06 61.79
223 372 16 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 57.54 49.78 59.67 49.51 61.29 58.27 59.22 61.44 59.17 58.93 58.94 59.01 58.12 58.30 60.13 57.29 60.11 57.24 57.32 60.46 61.06 60.99 61.99 62.59 62.45
272 372 16 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 59.13 61.71 61.17 61.65 62.19 59.84 49.92 50.31 93.02 61.47 60.00 60.01 60.50 59.16 61.99 59.22 60.74 56.91 58.54 61.51 61.90 61.47 59.72 62.73 62.63
275 372 16 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 60.15 61.26 61.70 61.53 58.55 49.01 91.90 59.13 61.76 90.60 50.30 61.93 59.76 60.81 61.86 59.53 49.50 59.81 60.27 59.61 61.78 61.22 62.20 62.65 62.50
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 59.56 50.81 59.58 61.70 61.99 59.85 59.30 62.70 59.29 61.99 59.71 59.47 59.91 58.97 60.83 59.24 48.63 58.33 59.95 59.65 61.43 62.59 60.43 62.79 61.59
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 58.39 59.87 59.27 62.34 58.04 59.76 59.26 60.81 59.23 59.02 60.27 61.99 59.34 58.97 59.24 88.45 61.26 59.33 62.19 59.67 62.48 61.77 61.64 62.06 62.83
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 60.37 61.99 60.27 61.93 59.31 59.63 59.95 62.88 59.57 61.76 60.22 60.94 61.31 61.03 61.50 51.78 61.61 59.56 61.13 59.16 61.45 62.34 62.26 62.32 62.44
339 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 59.69 59.80 59.77 62.57 60.67 59.88 50.94 62.16 60.37 59.71 61.20 62.06 91.19 62.41 61.99 59.90 59.43 59.79 62.57 62.64 62.60 62.55 59.72 62.66 62.64
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 59.86 63.40 59.77 61.99 59.31 59.76 60.29 62.26 90.90 59.79 62.64 60.11 50.28 59.85 59.95 60.11 62.09 59.23 51.82 59.99 62.55 62.34 59.05 50.08 62.30
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 59.85 62.64 60.19 62.06 59.95 60.77 59.53 59.95 59.83 60.09 59.90 61.20 59.62 90.22 48.12 51.38 59.66 59.65 62.64 60.67 60.26 63.04 62.79 62.77 61.85
400 372 16 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 58.23 61.42 50.98 61.27 60.37 50.98 60.97 60.58 61.09 59.97 59.64 61.03 48.74 60.63 48.12 59.02 61.78 61.13 61.31 60.53 62.71 62.19 62.31 61.80 61.20
403 372 16 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 50.32 60.97 50.23 49.71 60.79 49.58 50.76 60.23 50.46 57.10 58.12 60.42 57.96 60.90 60.63 58.96 60.82 59.09 50.55 49.75 61.34 61.35 59.80 48.12 61.06
412 372 16 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 48.12 58.35 60.46 61.51 60.20 50.50 57.90 61.76 48.44 61.43 60.00 61.09 59.24 61.41 60.82 60.51 61.22 61.61 58.66 61.17 62.75 63.77 62.60 62.36 62.33
415 372 16 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 49.89 50.35 59.81 60.23 59.83 58.92 57.83 60.34 56.28 59.05 51.46 49.82 57.73 59.40 59.78 50.38 57.17 57.42 56.98 51.21 60.14 60.89 52.23 61.27 61.76
464 372 16 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 59.76 62.32 50.50 48.12 62.09 49.74 58.89 61.53 59.13 61.42 62.64 59.62 59.38 59.75 60.55 59.72 61.50 61.76 61.65 61.29 62.55 61.17 62.76 62.88 61.90
467 372 16 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 59.49 62.32 59.59 61.22 62.00 60.37 59.45 61.42 62.00 59.13 60.27 61.99 59.52 60.95 62.00 59.87 60.67 58.39 60.01 84.80 61.85 61.88 53.93 61.82 61.95
476 372 16 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 59.57 61.99 58.85 59.80 59.61 49.46 57.71 62.06 50.01 59.36 61.70 61.75 59.30 58.53 61.18 58.92 61.08 59.76 60.48 61.93 61.28 62.09 60.74 62.72 61.88
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 59.23 60.81 59.32 62.32 59.43 59.85 59.22 61.54 50.51 58.64 59.95 61.59 59.54 60.61 59.34 59.42 59.30 89.32 59.52 58.53 60.79 63.09 60.23 63.04 63.06
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 59.56 59.80 62.32 59.50 60.12 60.01 60.08 60.50 59.69 59.86 59.71 62.84 60.73 61.53 61.70 60.53 61.56 59.58 62.97 62.06 62.66 63.04 62.57 62.03 62.53
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 59.96 60.17 59.47 59.36 59.57 61.30 60.00 61.52 60.83 60.03 61.07 62.41 60.29 60.08 61.48 60.33 61.01 60.27 59.80 88.43 60.26 63.02 62.45 62.36 61.87
540 372 16 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 60.84 61.99 60.12 61.93 59.77 62.90 59.95 63.26 51.66 61.70 61.13 62.26 60.94 61.20 61.99 61.20 61.23 60.03 51.00 62.32 50.26 62.82 62.87 63.16 62.84
543 372 16 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 59.91 62.39 62.16 60.38 60.26 60.87 60.34 62.41 62.41 62.09 62.32 59.95 60.09 62.75 61.11 59.33 61.76 59.71 60.32 51.11 62.32 62.66 62.75 62.52 62.97
592 372 16 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 90.89 87.19 91.88 92.19 92.40 90.84 90.40 91.41 91.95 55.90 93.62 89.64 90.60 57.93 54.74 90.15 85.03 89.90 83.56 89.80 89.05 58.56 65.99 85.74 57.15
595 372 16 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 91.26 93.07 93.93 91.50 93.65 89.62 80.45 85.15 93.88 95.17 89.31 92.46 93.00 92.11 76.38 89.63 91.97 91.53 91.45 92.45 91.90 75.02 90.43 90.16 92.62
604 372 16 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 92.92 95.24 92.46 92.29 90.71 85.02 86.14 92.72 92.47 90.30 89.77 92.31 92.05 91.62 59.66 93.62 93.82 53.12 92.74 92.25 92.28 88.82 92.45 92.28 91.07
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 92.03 89.70 93.79 87.17 92.63 92.17 94.31 90.61 90.18 91.18 92.74 88.70 89.96 90.60 59.16 89.14 59.19 92.65 84.24 85.92 90.98 90.51 90.19 91.88 59.20
656 372 16 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 92.69 64.33 95.27 83.76 93.84 89.18 94.57 91.28 91.61 91.73 92.08 88.68 90.58 92.47 88.55 92.43 87.03 92.24 91.34 92.05 94.50 89.64 91.25 92.14 93.63
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.94 93.02 94.02 91.73 93.67 91.16 93.56 92.34 93.53 94.10 91.68 93.23 90.68 93.24 85.87 93.77 91.67 94.26 91.34 93.87 94.04 92.40 91.06 59.76 92.98
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 90.09 89.83 94.95 92.58 94.22 92.98 93.77 59.19 89.68 94.24 93.43 90.63 95.19 92.18 93.14 93.84 91.38 91.87 92.23 94.45 93.09 92.76 91.65 60.71 93.31
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 94.85 93.50 94.33 93.60 88.74 92.37 95.52 91.14 93.30 93.32 93.02 91.58 94.45 94.75 93.96 90.74 89.82 93.46 92.81 89.46 91.90 58.98 93.01 92.55 91.92
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 92.67 94.38 93.64 94.11 94.49 93.21 91.39 89.39 93.59 93.39 94.72 93.42 94.50 87.86 93.49 91.52 91.68 93.76 91.13 92.58 61.03 93.21 94.43 93.94 89.78
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 95.18 92.56 88.21 90.99 91.86 92.64 94.47 93.97 92.58 92.19 92.14 91.85 92.77 94.48 51.17 94.34 94.34 92.46 92.37 93.06 61.74 92.58 91.18 94.59 92.67
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 92.88 91.41 90.16 48.12 93.75 93.14 93.74 91.06 93.60 92.77 93.67 90.63 92.24 90.56 95.45 87.41 91.94 92.89 90.92 91.74 91.13 91.46 93.77 92.72 91.90
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.10 93.45 95.77 91.04 89.61 92.23 93.37 92.65 92.79 93.95 89.07 93.26 90.39 92.84 91.41 93.56 90.51 90.42 92.16 92.91 92.24 92.53 61.10 92.86 70.81
784 372 16 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 49.59 60.88 60.23 60.24 61.56 61.62 57.51 60.71 49.69 61.03 60.62 50.37 57.60 60.74 60.07 62.32 60.48 61.29 59.91 60.67 62.05 61.05 61.18 61.68 62.21
787 372 16 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 57.42 61.60 60.77 60.66 60.85 59.81 58.00 59.61 58.49 60.71 51.39 62.03 90.11 59.51 61.20 59.22 60.69 59.64 61.31 58.30 62.28 62.75 62.08 61.95 61.91
796 372 16 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 58.55 61.60 49.53 61.75 60.88 58.07 58.93 61.07 58.70 60.20 59.43 61.65 58.54 60.86 60.16 60.98 60.32 57.33 60.47 61.29 61.48 61.68 61.63 61.90 61.46
799 372 16 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 58.01 48.94 59.93 59.32 59.95 57.79 56.60 59.78 58.79 56.55 58.80 49.92 57.28 59.53 59.07 56.76 59.98 48.74 57.70 50.00 59.72 59.96 63.10 61.11 60.30
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 59.79 60.97 58.64 61.99 61.87 59.63 58.63 59.17 58.51 49.68 59.66 62.32 59.43 59.56 61.65 59.57 60.29 58.74 60.03 59.07 62.48 62.14 62.34 62.99 61.94
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 59.99 61.99 61.65 61.93 59.41 59.71 59.19 59.66 58.19 58.54 60.06 62.70 59.47 59.61 61.48 59.04 62.56 59.64 60.15 58.56 60.63 61.83 59.88 62.58 62.11
860 372 16 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 58.97 61.94 59.22 59.81 59.25 59.80 51.79 63.04 59.57 61.83 61.99 62.06 59.62 62.55 61.09 61.07 60.99 61.70 60.39 59.91 61.90 62.02 52.12 62.44 62.66
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 59.70 59.15 59.57 62.39 60.27 60.02 59.38 62.32 59.42 59.56 62.97 59.32 59.97 60.72 61.93 59.58 61.70 59.52 61.93 50.96 62.34 62.57 87.88 62.15 62.13
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 59.91 62.06 59.85 60.22 59.62 59.02 93.12 60.03 60.08 90.77 50.51 61.71 59.62 59.21 62.06 60.37 59.90 59.62 60.27 61.99 62.25 62.69 62.39 61.78 62.75
915 372 16 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 59.88 62.32 59.57 50.86 59.43 62.64 92.75 59.96 51.47 59.61 60.67 62.39 60.09 61.99 61.43 92.17 59.81 59.57 60.01 61.99 62.42 62.92 62.75 62.66 61.62
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 59.45 59.70 61.74 59.72 59.21 60.33 61.20 62.41 59.81 59.50 51.47 62.72 60.34 58.92 61.87 59.85 61.61 59.98 60.22 62.32 61.55 62.32 62.79 62.50 61.81
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.42 52.56 59.93 62.39 59.43 59.33 60.53 50.74 60.65 59.57 62.97 61.93 51.36 60.72 61.76 50.40 61.66 60.86 60.83 59.53 62.36 62.57 60.44 63.09 62.44
976 372 16 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 59.23 61.33 61.34 61.19 60.65 57.11 61.44 61.07 49.14 60.88 59.40 61.60 48.37 59.62 60.61 49.16 63.79 60.59 50.39 48.12 60.94 61.18 51.39 61.94 61.50
979 372 16 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 60.48 60.78 57.58 61.44 61.76 58.02 50.37 60.34 49.20 61.05 59.15 49.82 58.51 60.91 60.65 57.99 60.52 59.01 58.87 49.97 62.15 61.82 62.02 61.69 62.16
988 372 16 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 50.20 61.29 61.50 61.78 60.07 58.67 58.29 61.98 60.87 61.33 60.30 61.12 59.32 59.49 60.30 50.16 59.31 58.67 58.28 61.06 61.87 61.39 61.54 62.96 62.35
991 372 16 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 57.86 60.77 60.52 61.33 59.70 48.01 58.47 60.85 60.41 58.75 60.00 56.63 57.73 58.78 60.58 60.01 59.03 50.57 56.11 50.25 61.76 62.11 61.63 61.96 61.10
1040 372 16 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 59.29 61.65 62.00 61.66 61.36 61.61 59.11 61.36 61.64 59.57 60.38 61.91 59.00 58.98 61.93 58.56 61.64 58.79 62.32 61.38 61.74 62.41 62.10 62.32 61.43
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 59.62 61.93 50.73 61.93 59.34 59.86 59.41 59.86 52.41 59.37 60.01 59.80 59.67 58.37 61.11 60.27 58.97 61.45 59.96 61.99 61.38 61.92 59.43 62.46 61.81
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 59.47 49.98 58.85 59.81 60.23 59.78 57.95 51.19 59.11 59.57 60.38 60.49 52.74 60.08 49.32 58.63 58.40 59.71 59.90 59.87 62.55 60.78 59.69 61.83 62.45
1055 372 16 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 59.78 59.83 61.67 60.72 61.59 59.83 59.00 48.12 61.93 59.83 62.64 62.32 59.92 60.66 61.74 59.28 61.60 58.92 61.13 61.87 62.67 62.55 52.64 62.24 62.26
1104 372 16 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 59.29 60.27 59.46 61.70 59.52 62.64 59.79 62.34 59.52 59.45 62.97 63.04 60.09 59.62 60.89 50.93 61.77 59.10 62.71 62.32 62.90 61.76 62.26 61.93 62.12
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 60.43 59.65 59.41 61.99 59.81 59.45 60.40 62.90 59.46 61.77 60.73 62.32 60.60 59.86 52.81 59.76 61.64 59.61 60.77 60.77 62.48 62.39 62.60 62.32 62.97
1116 372 16 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.94 62.26 60.58 61.93 59.86 60.61 59.87 62.05 62.64 62.20 61.43 62.64 59.62 62.64 61.01 60.38 62.19 49.50 60.78 61.93 62.27 62.43 62.27 62.73 62.97
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 60.32 61.01 59.62 59.48 59.80 60.77 59.48 62.26 60.77 60.89 49.99 60.00 59.57 60.03 61.45 90.79 59.71 60.81 60.77 61.94 62.91 62.03 62.71 62.68 51.89
1168 372 16 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 48.12 90.43 92.68 91.27 93.12 88.49 93.09 90.24 91.91 93.33 83.18 84.26 93.35 90.98 55.30 89.96 93.56 91.11 91.15 92.44 88.83 90.90 88.93 92.22 89.65
1171 372 16 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 93.36 90.00 94.23 89.30 95.29 57.43 92.12 59.09 94.51 93.18 92.68 90.24 92.49 75.69 76.10 93.72 58.12 93.65 76.69 89.83 90.29 90.65 93.71 87.09 92.58
1180 372 16 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 91.77 91.95 93.32 93.64 89.65 92.47 94.61 59.41 93.56 93.96 94.22 52.88 90.72 93.75 89.49 92.58 91.26 58.94 90.03 88.90 92.46 92.73 58.95 90.98 55.73
1183 372 16 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 90.13 91.74 93.70 90.35 93.46 88.42 89.63 93.10 92.42 92.38 89.48 88.16 94.35 92.66 91.64 90.89 58.20 89.07 91.24 87.34 92.33 90.88 91.66 53.81 59.89
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 91.98 90.81 94.19 90.04 89.78 91.23 93.26 91.17 93.62 89.31 93.19 87.83 94.32 92.77 70.81 94.43 90.43 90.22 90.41 91.43 82.66 92.47 92.91 91.48 90.61
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 89.49 86.62 93.62 67.86 93.02 92.15 93.44 90.97 90.61 94.83 92.54 89.83 93.51 91.92 89.66 93.63 96.14 94.86 94.15 91.40 93.39 93.46 93.06 59.77 91.23
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 91.54 92.46 93.30 91.73 95.96 93.78 93.88 93.63 89.45 93.43 91.94 90.88 90.20 91.56 90.04 94.46 92.45 91.51 93.73 91.80 92.01 86.17 92.01 91.54 92.13
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 94.20 95.16 93.76 92.47 94.85 94.95 91.46 93.41 94.73 94.36 93.38 91.38 90.08 89.94 93.46 93.53 95.17 92.90 93.26 93.37 91.25 92.30 93.47 91.38 88.62
1296 372 16 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 94.60 93.79 93.58 92.35 92.14 93.49 93.55 91.89 77.34 90.85 91.62 93.45 93.81 94.03 94.46 85.01 94.67 94.63 93.33 91.36 94.09 86.81 93.25 91.70 85.41
1299 372 16 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 94.48 91.95 94.10 95.68 91.33 93.16 95.01 96.11 94.37 91.72 93.19 92.23 93.95 94.74 94.36 95.88 91.65 92.78 92.42 94.19 94.52 93.49 92.28 60.84 93.55
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.05 91.36 94.72 92.68 90.38 93.68 93.75 92.71 92.64 94.20 93.13 94.55 94.07 93.98 91.67 92.87 92.13 94.84 94.51 92.39 92.34 91.87 89.13 62.26 87.81
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.36 92.41 91.80 89.90 90.39 92.37 94.18 94.33 93.04 93.96 91.64 93.59 92.92 95.46 92.38 92.40 90.95 92.07 92.96 93.30 91.36 95.07 88.88 93.09 92.51
1360 372 16 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 61.20 48.90 60.68 60.34 60.80 61.34 49.90 60.84 60.74 50.70 60.59 59.25 49.51 59.62 61.57 59.39 61.79 59.63 59.49 61.96 62.40 61.23 62.73 61.43 62.38
1363 372 16 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 59.97 60.74 61.04 61.79 61.11 61.37 50.49 61.29 60.47 61.46 58.84 62.32 59.16 49.62 61.02 58.19 60.57 58.55 61.67 61.99 62.38 62.24 61.84 62.13 62.17
1372 372 16 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 48.74 61.59 61.38 61.09 61.73 61.47 59.39 60.01 58.37 59.75 60.49 61.65 61.10 61.00 60.76 60.65 61.59 58.67 48.75 62.06 61.81 62.43 61.83 62.01 62.23
1375 372 16 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 50.26 59.99 60.61 61.01 60.13 59.87 56.90 59.66 59.59 59.80 49.42 61.37 58.25 57.37 60.12 61.70 60.83 60.36 60.56 50.72 62.05 61.43 60.54 62.63 61.77
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 58.84 60.78 61.47 59.25 61.70 59.43 58.95 61.75 58.57 61.66 59.62 61.93 59.53 59.87 61.41 59.27 90.45 58.23 58.15 58.63 59.16 63.20 62.67 62.50 61.37
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 59.52 61.87 59.93 61.71 61.94 60.61 59.14 62.14 58.97 61.99 59.25 59.52 59.67 59.52 60.63 59.87 62.28 59.01 59.48 61.90 62.32 62.55 50.39 61.94 62.03
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 59.18 62.08 59.27 59.20 59.79 59.92 59.49 61.71 62.06 59.41 59.90 59.58 59.99 58.74 61.76 59.99 61.55 59.33 62.64 59.88 62.45 62.55 61.35 62.46 61.76
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 58.99 59.72 59.33 61.59 59.20 59.78 59.23 62.24 58.32 61.98 60.84 59.90 59.14 61.95 62.06 59.43 59.84 58.74 51.80 59.95 61.56 62.22 61.64 62.39 62.03
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 60.04 61.75 59.80 59.81 61.99 50.27 59.95 61.77 59.55 59.66 60.77 88.17 59.69 62.41 62.64 91.16 60.96 58.88 60.43 62.26 62.46 63.04 59.57 62.34 62.61
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 93.44 62.32 62.64 61.79 59.80 59.18 59.69 60.13 59.70 59.57 61.20 61.07 59.33 59.91 60.90 59.71 61.32 59.57 60.22 60.32 62.55 63.11 62.72 61.64 62.26
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 59.09 60.32 59.82 62.64 59.19 60.37 59.53 61.76 51.03 59.61 60.67 61.26 60.80 60.72 62.64 59.23 60.95 59.56 62.97 62.50 62.72 61.39 62.17 62.80 61.33
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.52 59.79 59.14 59.95 59.80 60.87 52.36 62.97 59.37 62.03 62.97 62.39 60.97 61.21 62.32 59.61 61.70 59.71 59.98 59.62 60.25 62.75 62.48 62.72 62.20
1552 372 16 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 56.79 61.64 60.43 61.10 60.45 59.41 57.67 60.34 61.31 48.95 50.75 50.24 58.48 59.43 58.25 56.49 60.48 58.29 60.30 60.26 61.09 61.90 61.64 64.51 62.82
1555 372 16 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 58.39 61.11 59.19 61.56 61.90 61.26 58.63 61.99 58.34 60.57 60.64 59.87 58.16 60.52 60.03 50.14 57.63 58.19 58.80 60.97 63.04 61.31 52.02 62.48 62.28
1564 372 16 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 50.45 57.42 56.67 55.72 60.53 58.33 57.19 53.99 49.03 57.48 58.32 59.64 57.99 59.86 49.04 57.25 58.73 58.26 58.38 58.04 50.77 59.93 61.40 60.17 60.77
1567 372 16 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 57.48 60.80 60.90 59.45 61.99 56.69 58.34 60.69 60.73 51.33 57.89 50.39 58.36 60.96 60.44 49.33 58.31 58.67 60.63 58.36 61.12 61.74 61.14 62.99 60.68
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 83.53 88.44 84.88 85.08 85.08 89.43 84.85 90.33 84.04 87.40 86.57 87.65 85.39 88.88 88.49 87.10 87.04 87.07 88.05 90.21 89.57 89.90 86.93 88.73 88.68
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.08 88.34 83.96 87.54 88.65 88.35 85.47 85.72 84.54 88.33 87.71 86.85 82.69 87.69 88.06 86.95 87.56 88.23 87.94 88.60 88.42 89.57 88.92 88.46 89.61
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 86.99 56.21 89.61 87.22 85.27 86.52 84.44 86.52 84.84 87.05 89.35 88.93 86.18 86.93 90.46 88.28 90.32 87.66 87.77 92.33 87.06 87.15 89.89 89.03 87.86
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 84.47 83.01 85.60 85.18 85.28 87.60 85.33 86.50 87.33 87.77 89.77 90.62 84.97 87.59 85.17 86.55 88.49 85.67 90.47 91.00 86.41 90.04 88.63 89.31 91.02
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.48 86.20 85.22 84.23 82.40 85.49 83.94 86.14 84.96 90.00 85.69 89.30 88.31 90.67 86.05 87.08 86.65 85.99 88.84 91.57 88.34 89.37 88.76 90.95 87.33
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 84.83 83.87 85.88 85.94 84.20 86.71 83.54 88.89 86.68 85.46 90.01 86.19 86.43 86.14 88.75 88.74 89.55 86.60 90.65 87.92 89.38 89.22 88.77 90.98 88.30
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.26 86.21 86.70 86.64 86.79 88.41 83.54 87.94 85.52 87.25 86.95 88.36 86.00 87.76 87.40 88.76 85.35 87.11 89.34 87.46 87.33 89.84 90.51 88.31 88.02
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 84.63 88.42 83.59 84.03 87.12 84.90 84.35 87.86 87.60 85.67 90.03 84.55 87.08 43.72 90.41 86.71 86.93 88.59 86.21 87.19 89.49 88.83 86.98 89.67 86.19
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 85.78 85.10 87.06 85.85 85.75 86.08 87.05 86.50 88.49 85.51 89.27 85.33 88.33 88.43 89.13 88.14 87.98 89.70 90.01 87.96 89.56 88.86 89.76 89.34 88.81
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 85.33 55.49 85.95 86.99 82.75 86.35 83.79 88.80 90.37 83.49 87.88 92.20 87.57 85.43 90.77 87.66 89.01 89.83 88.83 88.65 87.71 88.24 89.60 89.37 89.74
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.39 85.29 84.06 88.72 85.74 90.04 87.22 87.87 86.75 87.21 84.39 52.60 85.86 86.53 89.72 87.72 84.87 86.44 88.54 89.61 87.53 88.71 88.63 87.39 91.23
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.38 84.40 86.42 87.16 83.94 89.47 85.43 86.50 87.49 88.84 92.23 85.77 87.70 84.63 84.99 88.64 88.38 85.77 88.99 87.56 87.51 87.63 86.90 94.54 89.58
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.86 88.25 85.90 83.87 84.58 85.85 85.17 88.22 85.54 86.28 91.55 88.28 88.10 85.41 86.97 87.23 86.29 87.53 91.86 87.80 89.01 89.03 87.46 88.34 90.09
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 84.04 86.42 83.62 87.03 84.32 86.52 86.53 85.36 88.58 84.96 87.46 88.42 86.99 86.31 87.64 86.45 90.35 88.16 90.52 91.09 94.45 87.99 88.48 88.75 86.83
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.04 89.27 86.62 86.82 86.33 91.31 84.03 89.00 88.66 86.85 90.99 87.54 87.29 87.78 89.05 86.66 87.18 88.10 88.82 93.96 91.12 89.24 87.17 55.98 90.02
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 82.65 85.25 84.79 43.72 83.75 87.82 84.32 88.47 84.22 84.95 90.98 87.10 88.02 88.46 85.99 88.04 86.45 86.56 85.51 87.03 88.77 89.08 87.96 89.26 88.93
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 83.55 85.74 84.63 84.88 82.47 88.00 84.12 87.47 86.10 87.44 90.31 87.43 89.65 85.66 88.47 85.50 90.54 84.64 89.04 89.56 90.07 89.50 88.34 90.37 91.10
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 83.67 84.79 86.13 86.58 85.21 88.42 85.83 88.01 87.18 87.61 88.45 88.65 86.86 87.87 88.30 55.25 43.72 88.15 87.41 88.98 88.66 88.26 88.39 91.72 89.32
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 86.13 85.61 83.84 89.78 86.49 84.58 86.42 87.88 84.90 88.74 87.54 91.68 87.17 86.77 43.72 86.43 43.72 89.07 89.56 90.28 88.86 88.90 88.16 90.41 88.53
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 83.43 85.49 84.57 84.11 88.36 88.90 85.41 84.37 85.14 85.20 91.59 89.12 85.76 86.73 87.82 88.02 87.14 87.13 88.27 87.58 88.95 89.00 89.24 90.10 90.54
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.45 84.66 84.54 83.12 86.23 84.71 86.29 86.77 87.14 88.42 87.90 90.15 88.27 85.89 87.39 87.71 87.08 87.84 86.64 92.44 89.17 90.39 86.94 90.74 89.45
Size of the All data:  (100, 28)
Size of the Sig data:  (21, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
9 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 91.98 90.81 94.19 90.04 89.78 91.23 93.26 91.17 93.62 89.31 93.19 87.83 94.32 92.77 70.81 94.43 90.43 90.22 90.41 91.43 82.66 92.47 92.91 91.48 90.61
3 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 89.49 86.62 93.62 67.86 93.02 92.15 93.44 90.97 90.61 94.83 92.54 89.83 93.51 91.92 89.66 93.63 96.14 94.86 94.15 91.40 93.39 93.46 93.06 59.77 91.23
14 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 91.54 92.46 93.30 91.73 95.96 93.78 93.88 93.63 89.45 93.43 91.94 90.88 90.20 91.56 90.04 94.46 92.45 91.51 93.73 91.80 92.01 86.17 92.01 91.54 92.13
6 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 94.20 95.16 93.76 92.47 94.85 94.95 91.46 93.41 94.73 94.36 93.38 91.38 90.08 89.94 93.46 93.53 95.17 92.90 93.26 93.37 91.25 92.30 93.47 91.38 88.62
12 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.94 93.02 94.02 91.73 93.67 91.16 93.56 92.34 93.53 94.10 91.68 93.23 90.68 93.24 85.87 93.77 91.67 94.26 91.34 93.87 94.04 92.40 91.06 59.76 92.98
7 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 90.09 89.83 94.95 92.58 94.22 92.98 93.77 59.19 89.68 94.24 93.43 90.63 95.19 92.18 93.14 93.84 91.38 91.87 92.23 94.45 93.09 92.76 91.65 60.71 93.31
11 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 94.85 93.50 94.33 93.60 88.74 92.37 95.52 91.14 93.30 93.32 93.02 91.58 94.45 94.75 93.96 90.74 89.82 93.46 92.81 89.46 91.90 58.98 93.01 92.55 91.92
17 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 89.84 95.59 89.30 92.87 93.64 91.45 93.72 94.63 96.05 95.10 93.32 85.38 93.42 48.12 58.32 78.79 94.49 91.95 93.05 92.38 60.28 92.39 93.12 92.61 91.61
0 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 94.39 90.90 90.83 91.65 95.27 92.45 94.89 93.57 94.36 93.48 92.70 92.33 92.09 94.71 93.37 95.36 90.57 91.30 92.74 92.52 58.52 92.53 91.34 92.05 93.06
15 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 93.84 90.64 93.37 91.47 93.39 92.08 94.27 93.29 94.14 91.98 93.36 92.09 91.38 94.82 87.58 93.06 93.73 92.79 92.79 94.12 92.66 95.30 91.86 52.60 59.48
16 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 95.19 89.90 91.66 93.81 92.61 91.11 93.92 92.79 92.28 92.95 91.71 93.93 94.13 91.67 94.56 93.28 96.33 93.17 92.52 92.19 93.98 93.16 93.88 92.57 68.90
4 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.05 91.36 94.72 92.68 90.38 93.68 93.75 92.71 92.64 94.20 93.13 94.55 94.07 93.98 91.67 92.87 92.13 94.84 94.51 92.39 92.34 91.87 89.13 62.26 87.81
8 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.36 92.41 91.80 89.90 90.39 92.37 94.18 94.33 93.04 93.96 91.64 93.59 92.92 95.46 92.38 92.40 90.95 92.07 92.96 93.30 91.36 95.07 88.88 93.09 92.51
1 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 92.67 94.38 93.64 94.11 94.49 93.21 91.39 89.39 93.59 93.39 94.72 93.42 94.50 87.86 93.49 91.52 91.68 93.76 91.13 92.58 61.03 93.21 94.43 93.94 89.78
13 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 95.18 92.56 88.21 90.99 91.86 92.64 94.47 93.97 92.58 92.19 92.14 91.85 92.77 94.48 51.17 94.34 94.34 92.46 92.37 93.06 61.74 92.58 91.18 94.59 92.67
18 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 92.88 91.41 90.16 48.12 93.75 93.14 93.74 91.06 93.60 92.77 93.67 90.63 92.24 90.56 95.45 87.41 91.94 92.89 90.92 91.74 91.13 91.46 93.77 92.72 91.90
5 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.10 93.45 95.77 91.04 89.61 92.23 93.37 92.65 92.79 93.95 89.07 93.26 90.39 92.84 91.41 93.56 90.51 90.42 92.16 92.91 92.24 92.53 61.10 92.86 70.81
19 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.08 92.56 95.00 91.98 95.50 89.95 92.75 93.10 94.56 93.18 92.63 92.37 94.71 94.65 88.54 92.71 48.12 93.22 89.43 91.09 91.74 92.48 92.68 56.57 92.61
20 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.33 96.36 91.19 93.37 95.37 92.15 95.07 93.06 93.12 93.08 93.84 92.27 91.78 86.90 48.12 95.65 48.12 91.03 92.12 92.25 93.78 93.49 92.86 91.47 92.20
10 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 91.04 94.11 90.14 92.09 94.27 93.11 93.46 91.67 95.06 94.48 92.71 92.29 94.73 92.03 94.63 94.35 93.27 94.86 92.34 92.36 93.98 94.02 94.16 92.60 90.30
2 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 92.42 88.17 93.81 88.32 93.18 93.06 92.77 93.30 94.09 93.37 91.78 92.68 91.98 95.89 94.92 93.97 92.23 93.10 93.33 91.20 93.22 92.72 92.72 90.34 93.27
Size of the test data:  (21, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.51 35.15 7.42 4.48 10.64 5.73 10.48 4.49 3.77 8.49 5.48 -0.11 3.81 9.39 -3.19 5.40 4.72 2.96 3.96 5.47 4.95 7.06 2.26 -36.77 -30.26 4
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 11.55 7.71 11.14 6.16 7.14 4.23 9.25 5.18 6.69 6.51 -1.24 5.83 0.74 7.18 2.94 8.06 -0.03 5.78 3.12 3.35 2.17 3.03 -27.24 2.49 -20.29 4
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.55 36.25 3.69 4.51 10.69 7.26 9.44 7.11 4.61 6.38 2.59 1.95 4.02 4.63 -0.42 6.18 2.13 3.85 5.96 -0.53 4.95 -0.98 2.12 2.51 4.27 3
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.14 3.29 1.59 4.17 5.53 1.33 10.44 4.97 3.92 5.34 1.15 4.31 5.48 6.70 -37.88 7.68 7.16 4.36 3.55 -0.90 -29.38 3.34 4.01 38.61 2.65 3
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 1.41 -1.72 9.66 -19.68 4.37 3.80 7.97 5.25 6.07 6.50 4.83 2.98 10.82 4.23 1.60 6.68 8.58 6.63 6.21 2.80 4.97 3.89 4.14 -28.69 1.62 3
80 372 16 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.21 7.17 5.71 8.84 6.52 6.55 9.37 6.77 8.45 9.43 3.29 0.83 6.34 4.40 -32.09 -7.92 7.56 3.36 6.84 5.19 -29.21 3.56 6.14 2.94 5.42 3
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.45 2.37 9.31 4.96 4.70 1.80 8.41 0.84 9.58 1.91 6.62 0.18 8.93 3.89 -17.68 7.33 3.39 3.15 2.36 1.22 -6.91 2.57 5.98 2.75 1.93 2
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.67 6.96 8.30 5.52 6.44 4.21 8.32 6.21 5.15 5.36 0.90 8.78 6.37 9.35 6.68 4.23 3.75 9.07 5.52 4.83 4.83 4.24 2.23 -32.28 -1.77 2
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.97 3.51 9.27 5.20 6.95 8.35 6.48 6.53 6.95 4.95 3.88 2.53 3.71 10.00 7.53 6.26 5.15 5.26 6.69 -1.24 4.05 2.33 5.78 -0.40 3.82 2
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.26 5.96 9.07 6.64 10.02 6.27 10.23 -29.70 3.00 8.78 3.42 4.44 8.76 6.04 4.39 5.10 1.83 5.27 1.58 6.53 3.71 3.54 2.88 -30.27 5.01 2
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.46 6.82 8.80 7.50 11.27 5.67 9.62 6.20 8.57 4.10 5.99 3.93 2.37 2.57 -0.18 6.69 5.02 8.27 2.50 2.30 5.70 3.03 2.30 -31.19 5.65 2
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.61 5.80 3.77 5.80 9.52 6.37 7.84 7.07 5.87 7.97 3.43 7.00 3.76 6.28 4.24 7.22 2.59 1.60 2.73 4.56 -31.04 3.67 1.58 2.71 4.25 1
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 11.59 7.29 7.63 6.96 1.95 3.96 11.98 3.20 7.78 6.07 6.07 3.22 8.45 6.99 6.56 1.98 4.47 6.35 3.47 2.00 4.57 -30.86 2.50 4.24 3.90 1
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.63 7.96 10.02 7.08 10.17 6.69 4.86 4.03 5.01 8.43 7.26 5.00 7.51 1.55 5.85 5.07 1.33 5.60 0.61 1.49 -33.42 5.22 5.95 5.19 2.95 1
732 372 16 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.23 6.16 5.37 4.40 10.00 5.32 9.42 2.59 9.38 7.82 2.69 3.53 4.22 2.10 9.46 -0.63 5.49 6.33 5.41 4.71 2.36 2.38 5.81 3.46 2.97 1
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.73 12.15 8.16 7.29 9.57 7.35 6.13 6.91 7.40 6.59 3.61 0.76 5.11 2.35 8.29 6.98 6.68 7.23 2.79 2.37 4.84 2.26 4.84 2.07 -2.40 1
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.41 7.77 8.87 5.40 10.29 1.53 6.92 5.09 7.38 5.57 4.18 3.72 7.85 6.78 0.24 37.46 4.40 5.07 2.02 2.11 3.08 4.22 4.29 -35.15 3.29 1
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.61 8.62 5.57 7.98 5.91 4.21 8.05 7.30 9.92 9.28 1.12 3.17 8.97 5.30 6.81 6.33 6.13 7.73 4.07 4.78 5.03 5.02 4.92 2.50 -0.24 1
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.80 4.61 7.60 5.09 6.87 1.07 6.70 4.92 5.53 5.74 7.32 41.33 8.27 5.14 4.84 5.56 11.46 6.73 3.98 2.58 6.45 4.45 5.25 5.18 -22.33 1
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.50 4.16 5.90 6.03 5.81 6.52 9.01 6.11 7.50 7.68 0.09 5.31 4.82 10.05 5.41 5.17 4.66 4.54 1.10 5.50 2.35 6.04 1.42 4.75 2.42 0
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.20 10.75 7.35 3.59 8.88 7.57 8.65 5.18 8.22 4.34 6.30 0.59 4.61 0.13 4.40 9.22 4.40 1.96 2.56 1.97 4.92 4.59 4.70 1.06 3.67 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_20 89.465714 1.991483
mAP_valid_zero_26 89.103810 1.376704
mAP_valid_zero_22 88.988095 0.804323
mAP_valid_zero_21 88.922381 1.681303
mAP_valid_zero_11 88.886667 2.086737
mAP_valid_zero_19 88.727143 1.544235
mAP_valid_zero_23 88.400952 1.061291
mAP_valid_zero_25 88.178571 7.532805
mAP_valid_zero_18 87.420952 1.337467
mAP_valid_zero_6 87.402857 1.854880
mAP_valid_zero_8 87.386667 1.411097
mAP_valid_zero_13 86.886667 1.502975
mAP_valid_zero_10 86.877619 1.599021
mAP_valid_zero_12 86.510476 8.012257
mAP_valid_zero_9 86.479524 1.709335
mAP_valid_zero_15 85.940476 9.809429
mAP_valid_zero_16 85.886667 7.073603
mAP_valid_zero_3 85.408095 1.440426
mAP_valid_zero_5 85.271905 1.728585
mAP_valid_zero_7 85.098571 1.143155
mAP_valid_zero_14 85.013333 9.564064
mAP_valid_zero 84.855714 1.427055
mAP_valid_zero_4 84.023333 9.386467
mAP_valid_zero_17 83.552381 13.333567
mAP_valid_zero_2 83.164762 9.231600


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_7 93.649524 1.008928
mAP_test_zero_10 93.412857 1.233787
mAP_test_zero_9 93.181905 1.647725
mAP_test_zero_5 93.045238 2.135703
mAP_test_zero 93.021905 1.786991
mAP_test_zero_13 92.835238 1.647351
mAP_test_zero_3 92.750952 2.094173
mAP_test_zero_18 92.711429 1.378370
mAP_test_zero_11 92.647619 1.155318
mAP_test_zero_16 92.555714 3.608916
mAP_test_zero_6 92.440476 1.101919
mAP_test_zero_19 92.395238 1.223747
mAP_test_zero_20 92.374762 1.149059
mAP_test_zero_2 92.152381 2.407048
mAP_test_zero_12 91.714286 2.104104
mAP_test_zero_8 91.017619 7.406802
mAP_test_zero_22 91.016667 7.545582
average_map 90.937048 1.388388
mAP_test_zero_23 90.870476 6.976633
mAP_test_zero_14 90.491905 9.993483
mAP_test_zero_4 88.686190 10.760625
mAP_test_zero_17 88.355714 13.504975
mAP_test_zero_26 87.986190 9.348518
mAP_test_zero_21 86.016190 12.960290
mAP_test_zero_15 85.359524 14.788780
mAP_test_zero_25 82.736190 15.756536
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 67.25 69.05 87.80 88.19 88.71 85.38 83.67 90.58 90.27 90.32 88.71 64.42 87.92 88.57 84.30 83.58 87.51 85.72 81.95 72.89 90.53 88.11 88.10 89.10 87.69
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 83.53 88.44 84.88 85.08 85.08 89.43 84.85 90.33 84.04 87.40 86.57 87.65 85.39 88.88 88.49 87.10 87.04 87.07 88.05 90.21 89.57 89.90 86.93 88.73 88.68
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.08 88.34 83.96 87.54 88.65 88.35 85.47 85.72 84.54 88.33 87.71 86.85 82.69 87.69 88.06 86.95 87.56 88.23 87.94 88.60 88.42 89.57 88.92 88.46 89.61
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 86.99 56.21 89.61 87.22 85.27 86.52 84.44 86.52 84.84 87.05 89.35 88.93 86.18 86.93 90.46 88.28 90.32 87.66 87.77 92.33 87.06 87.15 89.89 89.03 87.86
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 84.47 83.01 85.60 85.18 85.28 87.60 85.33 86.50 87.33 87.77 89.77 90.62 84.97 87.59 85.17 86.55 88.49 85.67 90.47 91.00 86.41 90.04 88.63 89.31 91.02
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 89.43 59.37 60.86 90.31 60.29 91.97 89.47 60.36 89.05 59.76 92.47 57.77 92.39 91.04 60.33 92.93 83.96 90.55 91.55 90.95 91.35 57.92 57.50 58.23 59.09
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 88.66 62.08 86.90 61.21 61.26 90.62 88.46 60.64 90.54 61.59 91.46 91.96 90.92 91.47 62.54 91.10 60.73 91.16 92.97 58.62 59.00 59.07 56.94 59.82 59.26
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 88.43 61.33 88.44 88.77 88.55 89.92 87.41 61.70 62.12 91.44 91.11 90.45 87.65 91.46 60.53 89.66 61.29 91.17 58.10 91.29 58.26 57.54 61.57 61.55 59.67
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 88.21 89.50 88.75 59.01 91.13 91.66 91.21 60.61 90.19 58.20 89.71 92.18 90.96 59.26 60.79 91.55 90.78 91.69 89.00 92.93 60.76 57.98 59.35 57.82 57.90
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 84.48 86.20 85.22 84.23 82.40 85.49 83.94 86.14 84.96 90.00 85.69 89.30 88.31 90.67 86.05 87.08 86.65 85.99 88.84 91.57 88.34 89.37 88.76 90.95 87.33
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 84.83 83.87 85.88 85.94 84.20 86.71 83.54 88.89 86.68 85.46 90.01 86.19 86.43 86.14 88.75 88.74 89.55 86.60 90.65 87.92 89.38 89.22 88.77 90.98 88.30
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 83.26 86.21 86.70 86.64 86.79 88.41 83.54 87.94 85.52 87.25 86.95 88.36 86.00 87.76 87.40 88.76 85.35 87.11 89.34 87.46 87.33 89.84 90.51 88.31 88.02
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 88.80 60.46 88.99 62.31 61.12 92.25 89.45 90.54 90.01 55.67 91.68 59.18 90.55 91.72 60.28 89.32 60.38 90.76 90.93 91.20 56.95 60.00 59.84 58.69 58.10
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 89.05 61.41 61.72 61.05 89.20 92.43 89.23 90.97 90.68 90.06 92.05 58.77 91.68 90.59 58.42 92.73 58.84 89.71 91.67 92.46 58.02 58.82 90.25 57.72 57.60
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 87.15 89.51 87.86 60.59 89.11 89.70 89.77 60.72 91.09 91.72 56.53 93.59 89.17 59.55 60.05 91.21 60.87 91.19 60.25 88.59 58.13 57.64 83.08 60.50 58.19
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 88.74 61.30 56.02 60.76 90.23 91.55 90.83 89.82 87.79 90.48 92.69 92.21 92.17 90.13 60.65 90.16 91.23 60.76 91.68 58.62 60.26 59.37 91.31 59.32 59.55
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 89.22 56.29 89.10 89.55 89.98 92.03 88.29 86.85 90.51 91.39 91.67 91.15 85.73 91.43 56.79 91.73 92.20 91.14 91.67 93.30 57.33 59.70 89.95 59.53 58.52
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 85.78 85.10 87.06 85.85 85.75 86.08 87.05 86.50 88.49 85.51 89.27 85.33 88.33 88.43 89.13 88.14 87.98 89.70 90.01 87.96 89.56 88.86 89.76 89.34 88.81
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 85.33 55.49 85.95 86.99 82.75 86.35 83.79 88.80 90.37 83.49 87.88 92.20 87.57 85.43 90.77 87.66 89.01 89.83 88.83 88.65 87.71 88.24 89.60 89.37 89.74
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 84.39 85.29 84.06 88.72 85.74 90.04 87.22 87.87 86.75 87.21 84.39 52.60 85.86 86.53 89.72 87.72 84.87 86.44 88.54 89.61 87.53 88.71 88.63 87.39 91.23
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 88.12 56.48 90.11 61.64 62.69 90.30 89.46 59.56 91.30 60.93 91.97 92.55 89.70 90.04 61.86 91.19 55.31 91.03 91.43 92.23 59.09 58.29 89.92 58.82 58.82
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 88.39 90.65 88.41 61.00 88.52 91.99 89.35 59.44 91.54 91.49 90.93 58.79 90.42 91.45 92.63 82.72 58.98 90.62 58.93 91.19 56.88 57.78 59.02 60.00 57.57
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 87.95 61.87 89.97 61.10 88.97 91.42 91.37 59.53 56.52 90.71 92.44 57.58 90.43 58.92 89.22 91.93 91.73 83.67 92.46 90.16 88.59 55.64 89.38 57.92 56.12
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 84.38 84.40 86.42 87.16 83.94 89.47 85.43 86.50 87.49 88.84 92.23 85.77 87.70 84.63 84.99 88.64 88.38 85.77 88.99 87.56 87.51 87.63 86.90 94.54 89.58
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 84.86 88.25 85.90 83.87 84.58 85.85 85.17 88.22 85.54 86.28 91.55 88.28 88.10 85.41 86.97 87.23 86.29 87.53 91.86 87.80 89.01 89.03 87.46 88.34 90.09
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 89.14 61.27 88.17 89.93 61.05 87.32 90.16 60.27 91.91 88.92 89.61 81.34 89.91 60.86 58.94 85.71 57.72 92.71 89.90 57.22 57.08 56.61 89.86 57.30 55.88
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 84.26 61.17 59.80 60.26 88.17 91.72 89.41 90.90 91.95 89.42 88.79 89.80 90.45 90.92 59.30 91.43 58.08 90.67 91.19 90.92 58.06 54.86 58.52 58.95 59.23
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 90.54 89.65 88.40 60.17 88.71 91.64 89.95 59.78 87.36 90.44 90.13 88.29 87.89 59.52 59.36 92.22 58.65 90.68 56.51 59.00 55.90 59.04 57.28 56.17 59.28
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 89.43 89.17 88.15 89.16 89.32 90.86 85.88 58.54 90.37 59.20 56.75 59.20 88.27 61.32 59.48 92.18 59.51 90.31 93.47 92.35 89.52 58.12 57.56 56.73 58.39
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 84.04 86.42 83.62 87.03 84.32 86.52 86.53 85.36 88.58 84.96 87.46 88.42 86.99 86.31 87.64 86.45 90.35 88.16 90.52 91.09 94.45 87.99 88.48 88.75 86.83
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 87.04 89.27 86.62 86.82 86.33 91.31 84.03 89.00 88.66 86.85 90.99 87.54 87.29 87.78 89.05 86.66 87.18 88.10 88.82 93.96 91.12 89.24 87.17 55.98 90.02
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 83.55 85.74 84.63 84.88 82.47 88.00 84.12 87.47 86.10 87.44 90.31 87.43 89.65 85.66 88.47 85.50 90.54 84.64 89.04 89.56 90.07 89.50 88.34 90.37 91.10
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.66 62.10 87.68 89.15 89.47 92.36 86.60 89.37 90.15 82.22 56.01 59.21 91.43 91.94 59.78 90.66 90.92 91.72 92.17 58.52 55.65 56.58 57.43 59.02 56.83
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.20 88.68 63.43 88.68 89.20 90.89 85.79 58.90 89.17 90.71 91.40 56.33 89.36 90.71 60.14 91.19 59.64 89.66 90.66 59.17 56.23 56.00 57.16 56.15 58.95
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 88.46 87.09 89.66 60.96 89.22 91.97 85.83 87.38 90.35 91.21 58.52 60.25 87.04 89.10 60.31 88.72 59.70 88.67 90.39 91.17 58.57 57.66 88.05 57.70 59.64
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 87.39 89.69 88.72 61.07 89.93 92.22 86.84 59.25 90.46 59.42 90.13 58.04 90.35 91.92 88.77 91.27 60.30 90.42 90.62 90.63 57.06 57.47 57.67 59.67 57.11
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 87.26 61.63 89.40 90.71 90.93 90.38 88.92 60.44 89.36 88.89 89.74 91.42 91.67 90.17 59.04 86.90 92.17 88.38 90.63 57.64 56.45 57.74 57.84 56.86 87.26
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 83.67 84.79 86.13 86.58 85.21 88.42 85.83 88.01 87.18 87.61 88.45 88.65 86.86 87.87 88.30 55.25 43.72 88.15 87.41 88.98 88.66 88.26 88.39 91.72 89.32
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 86.13 85.61 83.84 89.78 86.49 84.58 86.42 87.88 84.90 88.74 87.54 91.68 87.17 86.77 43.72 86.43 43.72 89.07 89.56 90.28 88.86 88.90 88.16 90.41 88.53
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 83.43 85.49 84.57 84.11 88.36 88.90 85.41 84.37 85.14 85.20 91.59 89.12 85.76 86.73 87.82 88.02 87.14 87.13 88.27 87.58 88.95 89.00 89.24 90.10 90.54
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 86.45 84.66 84.54 83.12 86.23 84.71 86.29 86.77 87.14 88.42 87.90 90.15 88.27 85.89 87.39 87.71 87.08 87.84 86.64 92.44 89.17 90.39 86.94 90.74 89.45
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 87.64 61.05 87.87 60.19 90.47 91.06 89.66 59.61 90.93 59.59 92.06 89.31 87.80 58.83 59.21 89.18 58.31 91.43 89.09 91.96 58.79 58.31 59.19 59.65 57.70
339 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 87.41 90.69 86.65 60.40 87.11 92.18 85.83 59.96 90.15 89.16 89.54 58.52 84.51 57.93 60.38 90.66 91.71 90.19 57.70 58.87 58.25 56.58 90.42 56.61 57.64
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 89.66 60.44 88.66 60.41 89.72 93.22 89.91 60.42 87.90 90.94 58.35 93.18 86.83 91.42 89.92 91.42 59.48 92.97 89.16 92.17 55.85 57.59 92.46 54.75 57.24
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 87.64 59.77 87.64 61.82 89.67 89.14 88.40 89.16 89.93 89.90 91.68 89.03 91.65 87.55 43.72 86.68 90.68 90.42 57.16 89.15 88.62 56.83 58.83 59.35 60.03
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 90.17 90.92 59.26 90.49 88.40 92.18 89.90 90.12 90.70 89.42 92.47 56.30 87.56 60.02 58.48 90.37 59.01 92.74 57.08 58.63 58.60 56.73 56.76 57.91 56.86
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 88.02 88.67 88.41 90.09 89.68 89.27 90.24 59.27 88.01 89.41 89.78 58.16 90.36 90.97 60.61 90.91 59.14 90.90 92.44 90.36 89.38 57.78 58.13 57.38 58.39
Size of the All data:  (100, 28)
Size of the Sig data:  (47, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
18 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 92.03 89.70 93.79 87.17 92.63 92.17 94.31 90.61 90.18 91.18 92.74 88.70 89.96 90.60 59.16 89.14 59.19 92.65 84.24 85.92 90.98 90.51 90.19 91.88 59.20
9 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 91.98 90.81 94.19 90.04 89.78 91.23 93.26 91.17 93.62 89.31 93.19 87.83 94.32 92.77 70.81 94.43 90.43 90.22 90.41 91.43 82.66 92.47 92.91 91.48 90.61
3 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 89.49 86.62 93.62 67.86 93.02 92.15 93.44 90.97 90.61 94.83 92.54 89.83 93.51 91.92 89.66 93.63 96.14 94.86 94.15 91.40 93.39 93.46 93.06 59.77 91.23
14 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 91.54 92.46 93.30 91.73 95.96 93.78 93.88 93.63 89.45 93.43 91.94 90.88 90.20 91.56 90.04 94.46 92.45 91.51 93.73 91.80 92.01 86.17 92.01 91.54 92.13
6 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 94.20 95.16 93.76 92.47 94.85 94.95 91.46 93.41 94.73 94.36 93.38 91.38 90.08 89.94 93.46 93.53 95.17 92.90 93.26 93.37 91.25 92.30 93.47 91.38 88.62
36 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 58.84 60.78 61.47 59.25 61.70 59.43 58.95 61.75 58.57 61.66 59.62 61.93 59.53 59.87 61.41 59.27 90.45 58.23 58.15 58.63 59.16 63.20 62.67 62.50 61.37
45 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 59.52 61.87 59.93 61.71 61.94 60.61 59.14 62.14 58.97 61.99 59.25 59.52 59.67 59.52 60.63 59.87 62.28 59.01 59.48 61.90 62.32 62.55 50.39 61.94 62.03
35 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 59.18 62.08 59.27 59.20 59.79 59.92 59.49 61.71 62.06 59.41 59.90 59.58 59.99 58.74 61.76 59.99 61.55 59.33 62.64 59.88 62.45 62.55 61.35 62.46 61.76
29 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 58.99 59.72 59.33 61.59 59.20 59.78 59.23 62.24 58.32 61.98 60.84 59.90 59.14 61.95 62.06 59.43 59.84 58.74 51.80 59.95 61.56 62.22 61.64 62.39 62.03
12 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 92.94 93.02 94.02 91.73 93.67 91.16 93.56 92.34 93.53 94.10 91.68 93.23 90.68 93.24 85.87 93.77 91.67 94.26 91.34 93.87 94.04 92.40 91.06 59.76 92.98
7 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 90.09 89.83 94.95 92.58 94.22 92.98 93.77 59.19 89.68 94.24 93.43 90.63 95.19 92.18 93.14 93.84 91.38 91.87 92.23 94.45 93.09 92.76 91.65 60.71 93.31
11 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 94.85 93.50 94.33 93.60 88.74 92.37 95.52 91.14 93.30 93.32 93.02 91.58 94.45 94.75 93.96 90.74 89.82 93.46 92.81 89.46 91.90 58.98 93.01 92.55 91.92
40 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 59.79 60.97 58.64 61.99 61.87 59.63 58.63 59.17 58.51 49.68 59.66 62.32 59.43 59.56 61.65 59.57 60.29 58.74 60.03 59.07 62.48 62.14 62.34 62.99 61.94
28 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 59.99 61.99 61.65 61.93 59.41 59.71 59.19 59.66 58.19 58.54 60.06 62.70 59.47 59.61 61.48 59.04 62.56 59.64 60.15 58.56 60.63 61.83 59.88 62.58 62.11
37 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 59.70 59.15 59.57 62.39 60.27 60.02 59.38 62.32 59.42 59.56 62.97 59.32 59.97 60.72 61.93 59.58 61.70 59.52 61.93 50.96 62.34 62.57 87.88 62.15 62.13
26 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 59.62 61.93 50.73 61.93 59.34 59.86 59.41 59.86 52.41 59.37 60.01 59.80 59.67 58.37 61.11 60.27 58.97 61.45 59.96 61.99 61.38 61.92 59.43 62.46 61.81
20 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 59.47 49.98 58.85 59.81 60.23 59.78 57.95 51.19 59.11 59.57 60.38 60.49 52.74 60.08 49.32 58.63 58.40 59.71 59.90 59.87 62.55 60.78 59.69 61.83 62.45
0 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 94.39 90.90 90.83 91.65 95.27 92.45 94.89 93.57 94.36 93.48 92.70 92.33 92.09 94.71 93.37 95.36 90.57 91.30 92.74 92.52 58.52 92.53 91.34 92.05 93.06
15 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 93.84 90.64 93.37 91.47 93.39 92.08 94.27 93.29 94.14 91.98 93.36 92.09 91.38 94.82 87.58 93.06 93.73 92.79 92.79 94.12 92.66 95.30 91.86 52.60 59.48
16 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 95.19 89.90 91.66 93.81 92.61 91.11 93.92 92.79 92.28 92.95 91.71 93.93 94.13 91.67 94.56 93.28 96.33 93.17 92.52 92.19 93.98 93.16 93.88 92.57 68.90
34 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 59.56 50.81 59.58 61.70 61.99 59.85 59.30 62.70 59.29 61.99 59.71 59.47 59.91 58.97 60.83 59.24 48.63 58.33 59.95 59.65 61.43 62.59 60.43 62.79 61.59
30 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 58.39 59.87 59.27 62.34 58.04 59.76 59.26 60.81 59.23 59.02 60.27 61.99 59.34 58.97 59.24 88.45 61.26 59.33 62.19 59.67 62.48 61.77 61.64 62.06 62.83
25 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 59.23 60.81 59.32 62.32 59.43 59.85 59.22 61.54 50.51 58.64 59.95 61.59 59.54 60.61 59.34 59.42 59.30 89.32 59.52 58.53 60.79 63.09 60.23 63.04 63.06
4 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 94.05 91.36 94.72 92.68 90.38 93.68 93.75 92.71 92.64 94.20 93.13 94.55 94.07 93.98 91.67 92.87 92.13 94.84 94.51 92.39 92.34 91.87 89.13 62.26 87.81
8 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 93.36 92.41 91.80 89.90 90.39 92.37 94.18 94.33 93.04 93.96 91.64 93.59 92.92 95.46 92.38 92.40 90.95 92.07 92.96 93.30 91.36 95.07 88.88 93.09 92.51
42 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 60.04 61.75 59.80 59.81 61.99 50.27 59.95 61.77 59.55 59.66 60.77 88.17 59.69 62.41 62.64 91.16 60.96 58.88 60.43 62.26 62.46 63.04 59.57 62.34 62.61
31 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 93.44 62.32 62.64 61.79 59.80 59.18 59.69 60.13 59.70 59.57 61.20 61.07 59.33 59.91 60.90 59.71 61.32 59.57 60.22 60.32 62.55 63.11 62.72 61.64 62.26
46 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 59.09 60.32 59.82 62.64 59.19 60.37 59.53 61.76 51.03 59.61 60.67 61.26 60.80 60.72 62.64 59.23 60.95 59.56 62.97 62.50 62.72 61.39 62.17 62.80 61.33
38 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.52 59.79 59.14 59.95 59.80 60.87 52.36 62.97 59.37 62.03 62.97 62.39 60.97 61.21 62.32 59.61 61.70 59.71 59.98 59.62 60.25 62.75 62.48 62.72 62.20
1 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 92.67 94.38 93.64 94.11 94.49 93.21 91.39 89.39 93.59 93.39 94.72 93.42 94.50 87.86 93.49 91.52 91.68 93.76 91.13 92.58 61.03 93.21 94.43 93.94 89.78
13 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 95.18 92.56 88.21 90.99 91.86 92.64 94.47 93.97 92.58 92.19 92.14 91.85 92.77 94.48 51.17 94.34 94.34 92.46 92.37 93.06 61.74 92.58 91.18 94.59 92.67
5 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 95.10 93.45 95.77 91.04 89.61 92.23 93.37 92.65 92.79 93.95 89.07 93.26 90.39 92.84 91.41 93.56 90.51 90.42 92.16 92.91 92.24 92.53 61.10 92.86 70.81
33 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 59.91 62.06 59.85 60.22 59.62 59.02 93.12 60.03 60.08 90.77 50.51 61.71 59.62 59.21 62.06 60.37 59.90 59.62 60.27 61.99 62.25 62.69 62.39 61.78 62.75
39 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 59.45 59.70 61.74 59.72 59.21 60.33 61.20 62.41 59.81 59.50 51.47 62.72 60.34 58.92 61.87 59.85 61.61 59.98 60.22 62.32 61.55 62.32 62.79 62.50 61.81
27 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.42 52.56 59.93 62.39 59.43 59.33 60.53 50.74 60.65 59.57 62.97 61.93 51.36 60.72 61.76 50.40 61.66 60.86 60.83 59.53 62.36 62.57 60.44 63.09 62.44
32 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 60.43 59.65 59.41 61.99 59.81 59.45 60.40 62.90 59.46 61.77 60.73 62.32 60.60 59.86 52.81 59.76 61.64 59.61 60.77 60.77 62.48 62.39 62.60 62.32 62.97
22 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 60.32 61.01 59.62 59.48 59.80 60.77 59.48 62.26 60.77 60.89 49.99 60.00 59.57 60.03 61.45 90.79 59.71 60.81 60.77 61.94 62.91 62.03 62.71 62.68 51.89
17 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 94.08 92.56 95.00 91.98 95.50 89.95 92.75 93.10 94.56 93.18 92.63 92.37 94.71 94.65 88.54 92.71 48.12 93.22 89.43 91.09 91.74 92.48 92.68 56.57 92.61
19 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 94.33 96.36 91.19 93.37 95.37 92.15 95.07 93.06 93.12 93.08 93.84 92.27 91.78 86.90 48.12 95.65 48.12 91.03 92.12 92.25 93.78 93.49 92.86 91.47 92.20
10 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 91.04 94.11 90.14 92.09 94.27 93.11 93.46 91.67 95.06 94.48 92.71 92.29 94.73 92.03 94.63 94.35 93.27 94.86 92.34 92.36 93.98 94.02 94.16 92.60 90.30
2 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 92.42 88.17 93.81 88.32 93.18 93.06 92.77 93.30 94.09 93.37 91.78 92.68 91.98 95.89 94.92 93.97 92.23 93.10 93.33 91.20 93.22 92.72 92.72 90.34 93.27
43 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 60.37 61.99 60.27 61.93 59.31 59.63 59.95 62.88 59.57 61.76 60.22 60.94 61.31 61.03 61.50 51.78 61.61 59.56 61.13 59.16 61.45 62.34 62.26 62.32 62.44
41 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 59.69 59.80 59.77 62.57 60.67 59.88 50.94 62.16 60.37 59.71 61.20 62.06 91.19 62.41 61.99 59.90 59.43 59.79 62.57 62.64 62.60 62.55 59.72 62.66 62.64
24 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 59.86 63.40 59.77 61.99 59.31 59.76 60.29 62.26 90.90 59.79 62.64 60.11 50.28 59.85 59.95 60.11 62.09 59.23 51.82 59.99 62.55 62.34 59.05 50.08 62.30
23 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 59.85 62.64 60.19 62.06 59.95 60.77 59.53 59.95 59.83 60.09 59.90 61.20 59.62 90.22 48.12 51.38 59.66 59.65 62.64 60.67 60.26 63.04 62.79 62.77 61.85
44 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 59.56 59.80 62.32 59.50 60.12 60.01 60.08 60.50 59.69 59.86 59.71 62.84 60.73 61.53 61.70 60.53 61.56 59.58 62.97 62.06 62.66 63.04 62.57 62.03 62.53
21 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 59.96 60.17 59.47 59.36 59.57 61.30 60.00 61.52 60.83 60.03 61.07 62.41 60.29 60.08 61.48 60.33 61.01 60.27 59.80 88.43 60.26 63.02 62.45 62.36 61.87
Size of the test data:  (47, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1052 372 16 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.75 -6.31 -30.25 -29.74 -29.75 -32.25 -30.34 -35.66 -31.40 -31.82 -31.29 -30.66 -32.99 -31.35 -7.47 -33.10 -33.80 -31.43 -31.77 -33.43 5.22 1.08 -30.26 2.30 3.93 21
284 372 16 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.56 -5.67 -30.53 0.06 -0.70 -30.45 -30.16 3.14 -32.01 1.06 -32.26 -33.08 -29.79 -31.07 -1.03 -31.95 -6.68 -32.70 -31.48 -32.58 2.34 4.30 -29.49 3.97 2.77 18
531 372 16 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.06 -28.50 -28.94 -30.73 -30.11 -27.97 -30.24 2.25 -27.18 -29.38 -28.71 4.25 -30.07 -30.89 0.87 -30.58 1.87 -30.63 -32.64 -1.93 -29.12 5.24 4.32 4.98 3.48 17
1119 372 16 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -26.94 -0.62 -29.78 -31.23 -31.13 -29.61 -29.44 1.82 -28.59 -28.00 -39.75 -31.42 -32.10 -30.14 2.41 3.89 -32.46 -27.57 -29.86 4.30 6.46 4.29 4.87 5.82 -35.37 17
479 372 16 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.72 -1.06 -30.65 1.22 -29.54 -31.57 -32.15 2.01 -6.01 -32.07 -32.49 4.01 -30.89 1.69 -29.88 -32.51 -32.43 5.65 -32.94 -31.63 -27.80 7.45 -29.15 5.12 6.94 17
927 372 16 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.04 -34.53 -29.73 1.43 -29.79 -32.64 -25.30 -36.64 -29.70 -31.64 4.45 1.68 -35.68 -28.38 1.45 -38.32 1.96 -27.81 -29.56 -31.64 3.79 4.91 -27.61 5.39 2.80 16
1043 372 16 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.12 0.63 -5.29 1.17 -30.89 -31.69 -31.42 -29.96 -35.38 -31.11 -32.68 -32.41 -32.50 -31.76 0.46 -29.89 -32.26 0.69 -31.72 3.37 1.12 2.55 -31.88 3.14 2.26 16
848 372 16 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.01 0.51 -30.35 -0.32 0.75 -32.62 -30.82 -31.37 -31.50 -5.99 -32.02 3.14 -31.12 -32.16 1.37 -29.75 -0.09 -32.02 -30.90 -32.13 5.53 2.14 2.50 4.30 3.84 16
851 372 16 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.06 0.58 -0.07 0.88 -29.79 -32.72 -30.04 -31.31 -32.49 -31.52 -31.99 3.93 -32.21 -30.98 3.06 -33.69 3.72 -30.07 -31.52 -33.90 2.61 3.01 -30.37 4.86 4.51 16
348 372 16 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.80 2.96 -28.89 1.58 -30.41 -33.46 -29.62 1.84 3.00 -31.15 4.29 -33.07 -36.55 -31.57 -29.97 -31.31 2.61 -33.74 -37.34 -32.18 6.70 4.75 -33.41 -4.67 5.06 16
1436 372 16 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.25 0.75 -29.17 -29.57 -28.76 -30.00 -27.92 0.01 -0.06 -32.03 -31.21 -30.87 -27.66 -32.72 1.23 -29.67 0.26 -31.84 4.54 -31.41 4.19 5.01 -0.22 0.91 2.09 16
351 372 16 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.79 2.87 -27.45 0.24 -29.72 -28.37 -28.87 -29.21 -30.10 -29.81 -31.78 -27.83 -32.03 2.67 4.40 -35.30 -31.02 -30.77 5.48 -28.48 -28.36 6.21 3.96 3.42 1.82 16
924 372 16 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.75 -28.98 -1.69 -28.96 -29.99 -30.56 -24.59 3.51 -29.36 -31.21 -39.93 6.39 -29.02 -31.79 1.73 -31.34 1.97 -29.68 -30.44 3.15 5.32 6.32 5.63 6.35 2.86 15
1439 372 16 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.22 -29.78 -29.42 2.58 -31.93 -31.88 -31.98 1.63 -31.87 3.78 -28.87 -32.28 -31.82 2.69 1.27 -32.12 -30.94 -32.95 -37.20 -32.98 0.80 4.24 2.29 4.57 4.13 15
1503 372 16 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.91 -29.38 -29.01 -29.21 -29.52 -29.99 -33.52 4.43 -31.00 2.83 6.22 3.19 -27.30 -0.11 2.84 -32.57 2.19 -30.60 -33.49 -32.73 -29.27 4.63 4.92 5.99 3.81 15
912 372 16 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.75 -0.04 -27.83 -28.93 -29.85 -33.34 6.52 -29.34 -30.07 8.55 -5.50 2.50 -31.81 -32.73 2.28 -30.29 -31.02 -32.10 -31.90 3.47 6.60 6.11 4.96 2.76 5.92 15
1427 372 16 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.14 -0.21 -26.97 0.50 0.68 -30.01 -29.32 1.50 -31.57 0.40 -32.21 -32.44 -31.25 -31.95 -1.91 -31.23 1.55 -32.15 -33.49 3.28 3.32 3.48 -6.55 2.12 2.77 15
1107 372 16 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -26.96 -30.04 -29.31 0.92 -30.12 -32.77 -26.44 3.65 -31.00 2.35 -29.40 4.28 -29.75 -32.06 -35.96 -31.51 1.34 -30.81 -29.85 -29.86 5.42 4.92 4.93 2.65 5.86 15
287 372 16 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.00 -30.78 -29.14 1.34 -30.48 -32.23 -30.09 1.37 -32.31 -32.47 -30.66 3.20 -31.08 -32.48 -33.39 5.73 2.28 -31.29 3.26 -31.52 5.60 3.99 2.62 2.06 5.26 14
1491 372 16 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.18 1.15 2.84 1.53 -28.37 -32.54 -29.72 -30.77 -32.25 -29.85 -27.59 -28.73 -31.12 -31.01 1.60 -31.72 3.24 -31.10 -30.97 -30.60 4.49 8.25 4.20 2.69 3.03 14
336 372 16 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.27 0.94 -27.60 1.74 -31.16 -31.43 -29.71 3.27 -31.36 2.17 -31.84 -28.37 -26.49 2.20 2.29 -37.40 3.30 -31.87 -27.96 -32.80 2.66 4.03 3.07 2.67 4.74 13
1424 372 16 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.59 1.41 0.61 -31.06 1.41 -32.54 -30.52 1.39 -30.48 1.90 -32.85 4.16 -32.86 -31.17 1.08 -33.66 6.49 -32.32 -33.40 -32.32 -32.19 5.28 5.17 4.27 2.28 13
528 372 16 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.61 -31.12 3.06 -30.99 -28.28 -32.17 -29.82 -29.62 -31.01 -29.56 -32.76 6.54 -26.83 1.51 3.22 -29.84 2.55 -33.16 5.89 3.43 4.06 6.31 5.81 4.12 5.67 13
863 372 16 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.45 -30.36 -28.29 1.80 -28.84 -29.68 -30.39 1.60 -31.67 -32.16 6.44 -34.27 -29.20 1.17 1.88 -31.63 0.83 -31.67 1.68 -37.63 4.21 4.93 4.80 1.65 3.94 13
1500 372 16 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -31.45 -29.33 -28.58 2.47 -29.52 -31.27 -30.42 1.98 -36.33 -30.83 -29.46 -27.03 -27.09 1.20 3.28 -32.99 2.30 -31.12 6.46 3.50 6.82 2.35 4.89 6.63 2.05 13
339 372 16 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.72 -30.89 -26.88 2.17 -26.44 -32.30 -34.89 2.20 -29.78 -29.45 -28.34 3.54 6.68 4.48 1.61 -30.76 -32.28 -30.40 4.87 3.77 4.35 5.97 -30.70 6.05 5.00 13
1488 372 16 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.10 0.48 -28.37 -30.12 0.94 -37.05 -30.21 1.50 -32.36 -29.26 -28.84 6.83 -30.22 1.55 3.70 5.45 3.24 -33.83 -29.47 5.04 5.38 6.43 -30.29 5.04 6.73 12
607 372 16 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 24.78 20.65 5.99 -1.02 3.92 6.79 10.64 0.03 -0.09 0.86 4.03 24.28 2.04 2.03 -25.14 5.56 -28.32 6.93 2.29 13.03 0.45 2.40 2.09 2.78 -28.49 5
735 372 16 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 11.55 7.71 11.14 6.16 7.14 4.23 9.25 5.18 6.69 6.51 -1.24 5.83 0.74 7.18 2.94 8.06 -0.03 5.78 3.12 3.35 2.17 3.03 -27.24 2.49 -20.29 4
92 372 16 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.51 35.15 7.42 4.48 10.64 5.73 10.48 4.49 3.77 8.49 5.48 -0.11 3.81 9.39 -3.19 5.40 4.72 2.96 3.96 5.47 4.95 7.06 2.26 -36.77 -30.26 4
723 372 16 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.14 3.29 1.59 4.17 5.53 1.33 10.44 4.97 3.92 5.34 1.15 4.31 5.48 6.70 -37.88 7.68 7.16 4.36 3.55 -0.90 -29.38 3.34 4.01 38.61 2.65 3
1235 372 16 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 1.41 -1.72 9.66 -19.68 4.37 3.80 7.97 5.25 6.07 6.50 4.83 2.98 10.82 4.23 1.60 6.68 8.58 6.63 6.21 2.80 4.97 3.89 4.14 -28.69 1.62 3
1244 372 16 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 4.55 36.25 3.69 4.51 10.69 7.26 9.44 7.11 4.61 6.38 2.59 1.95 4.02 4.63 -0.42 6.18 2.13 3.85 5.96 -0.53 4.95 -0.98 2.12 2.51 4.27 3
1308 372 16 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.67 6.96 8.30 5.52 6.44 4.21 8.32 6.21 5.15 5.36 0.90 8.78 6.37 9.35 6.68 4.23 3.75 9.07 5.52 4.83 4.83 4.24 2.23 -32.28 -1.77 2
159 372 16 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.97 3.51 9.27 5.20 6.95 8.35 6.48 6.53 6.95 4.95 3.88 2.53 3.71 10.00 7.53 6.26 5.15 5.26 6.69 -1.24 4.05 2.33 5.78 -0.40 3.82 2
1232 372 16 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.45 2.37 9.31 4.96 4.70 1.80 8.41 0.84 9.58 1.91 6.62 0.18 8.93 3.89 -17.68 7.33 3.39 3.15 2.36 1.22 -6.91 2.57 5.98 2.75 1.93 2
659 372 16 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.46 6.82 8.80 7.50 11.27 5.67 9.62 6.20 8.57 4.10 5.99 3.93 2.37 2.57 -0.18 6.69 5.02 8.27 2.50 2.30 5.70 3.03 2.30 -31.19 5.65 2
668 372 16 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 5.26 5.96 9.07 6.64 10.02 6.27 10.23 -29.70 3.00 8.78 3.42 4.44 8.76 6.04 4.39 5.10 1.83 5.27 1.58 6.53 3.71 3.54 2.88 -30.27 5.01 2
1247 372 16 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 9.73 12.15 8.16 7.29 9.57 7.35 6.13 6.91 7.40 6.59 3.61 0.76 5.11 2.35 8.29 6.98 6.68 7.23 2.79 2.37 4.84 2.26 4.84 2.07 -2.40 1
144 372 16 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.41 7.77 8.87 5.40 10.29 1.53 6.92 5.09 7.38 5.57 4.18 3.72 7.85 6.78 0.24 37.46 4.40 5.07 2.02 2.11 3.08 4.22 4.29 -35.15 3.29 1
156 372 16 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 7.61 8.62 5.57 7.98 5.91 4.21 8.05 7.30 9.92 9.28 1.12 3.17 8.97 5.30 6.81 6.33 6.13 7.73 4.07 4.78 5.03 5.02 4.92 2.50 -0.24 1
720 372 16 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.63 7.96 10.02 7.08 10.17 6.69 4.86 4.03 5.01 8.43 7.26 5.00 7.51 1.55 5.85 5.07 1.33 5.60 0.61 1.49 -33.42 5.22 5.95 5.19 2.95 1
671 372 16 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 11.59 7.29 7.63 6.96 1.95 3.96 11.98 3.20 7.78 6.07 6.07 3.22 8.45 6.99 6.56 1.98 4.47 6.35 3.47 2.00 4.57 -30.86 2.50 4.24 3.90 1
83 372 16 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.61 5.80 3.77 5.80 9.52 6.37 7.84 7.07 5.87 7.97 3.43 7.00 3.76 6.28 4.24 7.22 2.59 1.60 2.73 4.56 -31.04 3.67 1.58 2.71 4.25 1
95 372 16 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 10.80 4.61 7.60 5.09 6.87 1.07 6.70 4.92 5.53 5.74 7.32 41.33 8.27 5.14 4.84 5.56 11.46 6.73 3.98 2.58 6.45 4.45 5.25 5.18 -22.33 1
147 372 16 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.20 10.75 7.35 3.59 8.88 7.57 8.65 5.18 8.22 4.34 6.30 0.59 4.61 0.13 4.40 9.22 4.40 1.96 2.56 1.97 4.92 4.59 4.70 1.06 3.67 0
1311 372 16 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 8.50 4.16 5.90 6.03 5.81 6.52 9.01 6.11 7.50 7.68 0.09 5.31 4.82 10.05 5.41 5.17 4.66 4.54 1.10 5.50 2.35 6.04 1.42 4.75 2.42 0

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_6 89.582340 2.443592
mAP_valid_zero_18 88.547447 4.713353
mAP_valid_zero_13 88.389149 2.257730
mAP_valid_zero_16 88.259149 5.483069
mAP_valid_zero_9 87.331064 6.394417
mAP_valid_zero_7 87.227447 2.370679
mAP_valid_zero 86.595106 3.586833
mAP_valid_zero_11 86.467872 10.379424
mAP_valid_zero_19 85.155532 11.666241
mAP_valid_zero_5 84.694681 8.488761
mAP_valid_zero_20 83.973404 12.901407
mAP_valid_zero_3 83.660000 9.282097
mAP_valid_zero_10 83.540851 11.318962
mAP_valid_zero_14 83.232128 11.819109
mAP_valid_zero_12 79.447872 14.828596
mAP_valid_zero_4 77.781277 13.030367
mAP_valid_zero_23 77.762766 14.911936
mAP_valid_zero_8 77.308085 13.906354
mAP_valid_zero_2 76.469787 13.577989
mAP_valid_zero_17 75.532979 15.960938
mAP_valid_zero_21 74.431277 15.860655
mAP_valid_zero_15 73.067660 15.433913
mAP_valid_zero_26 72.012128 15.565705
mAP_valid_zero_22 70.991489 15.657550
mAP_valid_zero_25 70.979574 15.738005


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_16 74.908404 17.186230
mAP_test_zero_7 74.803032 17.581260
mAP_test_zero_10 74.783830 16.537339
mAP_test_zero_12 74.731809 15.054400
mAP_test_zero 74.519149 16.663832
mAP_test_zero_20 74.303032 15.941213
mAP_test_zero_22 74.287766 14.747048
mAP_test_zero_9 74.282979 17.156531
mAP_test_zero_5 74.170532 16.436209
mAP_test_zero_13 74.121649 16.817738
mAP_test_zero_23 73.978191 15.824531
mAP_test_zero_3 73.966064 16.483464
mAP_test_zero_11 73.848936 16.349771
mAP_test_zero_14 73.845106 16.193388
mAP_test_zero_19 73.643298 16.140287
average_map 73.643030 14.836877
mAP_test_zero_8 73.638138 15.959009
mAP_test_zero_2 73.575851 15.724723
mAP_test_zero_18 73.463989 16.616144
mAP_test_zero_6 73.380266 16.421872
mAP_test_zero_26 73.023404 14.328836
mAP_test_zero_4 72.689202 15.402309
mAP_test_zero_17 72.668564 16.378359
mAP_test_zero_21 72.616170 14.914739
mAP_test_zero_25 71.057819 14.460644
mAP_test_zero_15 70.768564 15.483869


Summary using radar plot

Code
res1_valid['id'] = res1_valid.index.to_series().apply(extract_number)
res1_test['id'] = res1_test.index.to_series().apply(extract_number)



res_comb = pd.concat([res1_valid,res1_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res1_test = res1_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range1 = np.array(list(res1_valid['mean']) + list(res1_test['mean']))

categories = [str(i) for i in range(1,26)]

fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res1_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res1_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()




##############


res2_valid['id'] = res2_valid.index.to_series().apply(extract_number)
res2_test['id'] = res2_test.index.to_series().apply(extract_number)


res_comb = pd.concat([res2_valid,res2_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res2_test = res2_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res2_valid['mean']) + list(res2_test['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res2_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res2_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()

best_valid_bit_size_16 = round(res1_valid['mean'][0])
id_best_valid = res1_valid['id'][0]
best_test_bit_size_16 = list(round(res1_test.query('id == @id_best_valid')['mean'],2))[0]

best_valid_bit_size_16_mw = round(res2_valid['mean'][0])
id_best_valid = res2_valid['id'][0]
best_test_bit_size_16_mw = list(round(res2_test.query('id == @id_best_valid')['mean'],2))[0]




The results in this presentation are from two experimental designs:

The thresholding is based on fixed values between -1 and 1 on a step size of 0.1.

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
0 372 8 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 65.21 63.17 63.44 63.04 52.78 59.88 63.32 60.91 60.67 61.82 60.93 64.43 58.38 58.88 62.46 58.99 61.72 63.82 60.18 63.30 67.91 60.79 60.67 62.62 65.74
3 372 8 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 54.76 57.74 62.70 62.66 62.12 57.95 63.68 60.39 65.12 60.03 58.52 56.98 60.54 56.37 60.95 43.72 63.32 61.39 58.17 56.56 64.19 65.18 60.32 58.16 60.33
12 372 8 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 56.36 43.72 69.57 64.69 62.58 62.35 57.81 62.85 66.27 58.15 43.72 62.19 61.92 64.66 64.56 61.61 64.14 60.49 62.02 57.84 60.34 43.72 65.59 64.62 63.26
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 65.64 65.06 64.95 65.96 64.71 62.16 78.06 57.81 63.14 65.11 63.03 62.97 65.27 64.14 64.50 61.53 63.07 69.06 59.89 59.13 64.92 67.46 65.81 66.75 69.14
64 372 8 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 55.28 43.72 87.33 63.49 62.86 56.05 88.30 58.71 63.75 65.12 58.90 60.04 89.95 55.99 60.43 60.67 60.64 59.96 56.73 59.34 66.49 68.13 61.54 61.95 58.24
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.26 62.62 86.84 61.63 60.48 43.72 57.24 61.21 87.21 64.21 88.46 59.04 61.32 58.84 59.32 90.48 61.27 88.08 92.21 56.29 60.43 60.39 59.65 59.73 59.58
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 64.71 60.70 62.10 87.85 61.14 91.88 88.30 59.57 43.72 87.16 59.27 92.18 84.02 59.93 61.20 88.62 60.33 59.00 90.56 55.89 59.57 60.94 56.45 60.44 61.52
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 88.57 62.53 86.74 61.84 61.35 92.60 88.93 61.47 89.55 62.20 92.17 59.70 84.94 62.20 43.72 60.71 59.85 61.03 59.30 58.30 64.25 62.34 59.50 62.20 58.68
128 372 8 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 62.03 61.34 60.30 61.36 63.42 56.16 60.56 60.65 88.97 60.91 59.58 57.89 89.23 60.05 59.88 92.08 59.57 60.55 56.38 57.96 58.51 58.41 57.68 59.23 57.82
131 372 8 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 88.93 61.65 86.30 61.21 62.11 59.05 88.19 51.70 56.80 55.28 58.69 57.99 90.41 60.40 58.68 60.03 59.32 89.00 59.30 88.92 57.61 59.95 57.11 59.23 58.37
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 89.47 61.30 61.12 62.20 87.85 90.42 89.08 61.95 60.60 82.15 89.54 57.66 91.40 60.55 61.03 88.85 92.48 60.05 58.38 58.68 57.06 62.07 90.09 59.18 57.38
143 372 8 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 60.70 64.71 61.81 88.72 59.45 59.74 88.60 59.60 60.91 62.62 91.43 59.14 90.95 60.33 60.39 84.69 57.49 89.97 43.72 58.65 56.85 59.50 58.97 58.05 59.58
192 372 8 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 56.60 60.72 56.22 64.49 64.99 58.72 54.20 58.36 56.72 58.84 64.00 64.20 76.61 61.93 60.92 63.18 63.06 60.21 59.64 59.31 64.38 60.91 61.52 61.16 60.14
195 372 8 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 86.22 56.44 59.08 61.09 57.09 54.34 87.14 58.01 59.11 58.59 56.23 54.75 88.02 57.93 57.87 90.35 50.34 59.48 57.45 55.60 62.30 61.45 58.33 58.53 56.75
204 372 8 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 67.39 56.73 66.55 64.54 63.55 66.39 43.72 62.84 64.68 65.99 57.00 43.72 56.97 63.82 60.90 43.72 64.60 65.03 59.62 58.64 67.02 62.37 60.67 66.36 56.81
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 67.68 68.93 68.88 67.94 67.85 66.44 69.21 64.78 66.59 64.92 67.51 63.61 67.26 64.58 66.57 71.89 69.79 66.18 65.79 63.18 65.28 71.54 67.96 68.13 68.20
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.22 64.25 87.63 63.04 63.92 60.11 88.64 62.74 64.17 87.34 60.43 57.99 87.00 61.27 64.76 92.24 59.90 56.52 59.80 92.46 59.68 60.61 61.01 57.17 59.93
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 64.49 63.25 61.96 61.22 62.59 89.97 88.17 63.16 89.63 62.17 91.99 58.58 61.24 55.73 62.05 46.94 62.82 59.63 59.87 89.60 63.15 63.13 60.36 51.48 59.83
268 372 8 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 57.08 59.16 55.69 60.26 87.42 59.67 43.72 60.87 60.78 63.24 91.42 56.86 90.45 60.30 59.62 61.87 60.96 61.55 58.48 56.09 62.65 61.76 58.42 59.90 58.83
271 372 8 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 84.02 61.12 62.67 87.69 62.23 90.67 43.72 58.39 62.31 89.64 57.26 58.96 90.51 58.56 57.35 90.30 61.59 59.78 57.43 57.88 60.98 60.34 60.88 60.26 59.15
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 88.33 64.65 62.29 61.26 62.48 57.16 86.62 61.54 90.72 61.19 59.23 43.72 91.18 59.52 61.15 90.49 59.75 91.46 60.88 58.32 59.05 63.79 60.61 60.63 57.94
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 88.35 61.48 86.23 60.74 59.33 90.19 90.24 59.94 60.55 61.32 59.04 56.87 88.98 58.24 58.85 59.08 59.01 91.17 93.15 56.00 59.11 58.23 59.09 60.54 60.49
332 372 8 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 63.65 62.59 62.77 62.35 54.88 59.18 89.30 87.40 81.90 59.19 59.52 56.41 87.31 59.22 60.06 61.12 59.85 92.87 56.58 58.85 57.36 61.07 59.49 57.73 59.46
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 88.57 60.13 60.22 61.27 89.95 58.07 90.81 60.70 90.41 90.49 58.59 60.34 82.30 57.75 60.22 91.60 60.09 55.97 57.90 55.78 59.52 61.56 56.52 58.71 59.57
384 372 8 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 43.72 63.23 59.14 60.74 61.19 59.62 87.09 60.39 61.71 58.80 59.24 60.09 61.28 51.72 58.53 61.14 63.53 57.64 50.50 58.81 59.70 61.13 62.95 58.74 62.90
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 68.45 66.44 57.87 62.97 57.16 43.72 79.22 78.65 63.73 65.90 62.13 60.09 89.08 60.59 63.28 54.04 63.36 64.43 57.30 61.77 63.84 61.54 64.79 67.58 60.06
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 67.38 63.45 66.94 67.16 65.95 59.19 56.12 64.03 66.74 64.89 57.94 65.81 59.34 86.95 61.57 65.74 64.13 66.61 61.11 66.23 65.37 65.37 62.85 67.57 65.24
399 372 8 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 83.10 62.62 61.91 53.71 60.73 82.66 54.56 53.37 58.61 58.43 56.55 55.61 87.32 60.34 60.79 59.95 58.87 89.28 56.05 55.64 59.89 59.42 59.44 61.00 61.00
448 372 8 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 55.60 62.13 62.42 59.34 61.50 58.40 85.28 60.54 61.05 89.74 90.96 58.29 89.42 63.18 61.85 89.23 61.40 61.25 58.81 58.62 57.76 61.72 61.68 62.71 59.37
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 88.14 62.84 61.63 60.46 88.38 58.93 89.46 88.86 61.80 61.29 59.60 58.61 89.41 59.21 61.06 55.82 59.76 89.98 58.68 87.52 63.16 61.20 60.36 58.98 60.35
460 372 8 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 62.67 62.25 59.80 63.73 60.95 58.72 87.94 61.41 61.33 61.80 56.90 88.06 88.81 60.84 60.82 56.16 61.57 59.62 60.02 58.75 62.16 58.56 62.15 59.11 59.52
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 89.13 62.47 61.20 62.12 62.08 58.95 87.86 62.03 89.96 62.83 61.02 55.65 43.72 60.36 61.93 92.22 63.77 60.02 58.25 56.71 61.97 57.70 88.11 61.05 60.48
512 372 8 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 88.05 60.63 62.90 61.37 62.77 90.72 62.94 59.83 62.66 62.24 58.92 57.94 43.72 59.72 60.89 81.90 60.98 59.81 59.28 60.36 59.35 60.99 61.19 58.64 58.74
515 372 8 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 64.30 62.68 56.39 61.62 61.85 91.93 89.97 61.43 91.16 60.66 58.14 55.66 86.05 59.59 61.17 85.13 63.22 60.63 59.68 59.13 59.96 60.77 57.69 57.76 59.63
524 372 8 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 85.94 62.43 61.67 61.85 61.70 88.70 88.42 60.99 90.72 61.07 91.47 56.56 61.31 58.08 60.61 55.24 61.79 91.22 56.56 55.89 58.00 59.59 59.73 58.32 59.35
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 88.01 62.31 62.86 62.19 62.80 59.34 88.41 61.60 91.55 85.37 61.19 59.33 90.96 60.55 60.55 88.35 59.50 60.20 59.18 58.00 88.72 58.71 59.77 59.87 56.81
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 67.58 66.82 66.14 66.51 74.73 61.83 57.37 67.78 69.95 68.43 62.89 66.38 70.33 65.18 65.88 63.67 68.64 65.64 61.94 62.41 67.30 66.56 69.13 66.34 68.04
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 58.62 62.09 65.54 66.28 61.68 60.81 65.21 61.38 59.34 64.62 59.60 59.97 62.47 59.40 64.30 64.62 64.82 61.93 60.60 59.91 66.04 64.38 64.45 67.52 63.01
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.53 62.74 64.39 64.03 86.68 60.35 65.91 62.88 63.17 63.80 60.97 61.54 62.83 61.20 65.91 60.72 60.69 63.47 60.69 58.51 63.84 64.44 62.72 64.53 62.64
591 372 8 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 87.82 61.15 63.85 65.91 66.36 43.72 58.43 63.10 65.90 65.99 63.33 59.86 63.16 59.63 61.53 63.75 56.38 65.10 61.91 60.13 65.01 43.72 43.72 62.59 61.89
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 86.78 62.72 64.46 62.61 88.36 59.86 60.86 60.01 63.54 90.09 91.73 57.20 91.82 60.32 60.06 60.89 60.79 63.65 57.56 59.02 63.41 62.58 59.24 63.81 63.14
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 63.48 65.16 64.33 64.38 64.33 89.10 88.51 61.65 43.72 63.83 58.95 60.21 63.52 62.82 63.10 88.23 60.38 84.69 60.37 59.06 62.90 64.29 60.74 60.24 62.88
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.67 64.49 61.42 62.08 60.72 90.32 86.21 59.43 88.09 61.24 90.18 59.40 90.28 59.57 62.97 60.40 61.65 58.75 59.69 58.14 59.88 62.49 58.55 60.71 62.26
655 372 8 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 60.99 61.79 63.98 60.98 63.08 43.72 63.70 58.97 62.03 62.99 59.46 59.76 87.64 60.93 61.28 60.69 63.07 64.57 56.54 58.96 62.21 62.36 62.14 60.79 60.87
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 65.25 62.53 62.98 88.91 63.72 59.18 66.74 61.76 63.52 64.78 91.15 60.24 91.00 61.57 61.56 91.71 61.03 90.47 57.54 91.96 65.10 58.98 60.12 58.59 65.50
707 372 8 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 86.35 62.85 61.44 61.59 87.12 59.82 87.94 60.66 56.85 61.07 59.00 60.06 90.95 59.56 61.09 92.23 60.74 61.24 58.62 58.07 60.56 58.11 59.27 57.87 59.97
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 88.62 62.81 63.61 43.72 88.97 90.42 87.91 60.78 85.04 89.48 60.52 57.91 89.44 57.22 59.08 86.23 59.34 60.60 57.05 92.21 87.43 58.46 58.25 60.01 59.03
719 372 8 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 63.03 87.05 56.42 62.66 88.59 58.44 90.22 59.83 61.53 60.80 55.15 59.01 90.54 58.68 63.21 61.24 59.99 91.11 60.77 89.13 59.43 58.44 61.41 60.70 62.49
768 372 8 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 60.35 61.77 62.98 61.43 54.76 58.52 54.14 43.72 63.84 58.63 57.32 58.21 43.72 60.32 58.17 84.57 60.23 58.70 59.88 56.39 63.12 61.61 62.82 57.44 58.26
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 65.44 61.40 61.10 65.25 64.80 59.64 63.15 63.02 64.78 61.44 60.84 59.71 87.78 62.64 62.34 63.80 62.27 61.76 58.18 59.43 64.48 63.84 62.32 66.20 66.27
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 65.55 65.59 64.78 61.61 64.71 59.20 54.62 64.38 64.49 66.82 63.20 58.30 61.61 61.87 61.80 62.71 61.54 63.85 59.75 59.95 62.30 63.18 63.15 62.75 62.69
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 66.47 64.73 63.32 64.49 64.87 62.01 66.87 64.63 64.15 62.51 59.20 59.03 64.50 62.32 63.84 67.19 65.54 63.40 59.49 57.50 67.09 63.80 68.22 65.74 67.35
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 63.11 64.46 88.09 62.35 62.15 62.14 82.81 63.12 49.89 63.73 87.53 61.40 63.48 61.57 62.47 63.82 61.98 61.60 60.14 91.03 64.82 61.79 61.32 59.75 61.32
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 87.47 62.41 89.51 89.18 63.55 61.14 89.94 83.67 86.95 61.73 91.83 56.81 90.30 60.45 58.77 61.30 59.06 58.12 56.86 58.99 60.80 58.11 60.52 59.49 57.66
844 372 8 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 56.19 60.34 55.93 87.87 60.62 58.52 87.07 60.16 62.49 60.30 57.77 58.22 89.48 59.85 60.94 88.32 51.13 60.49 58.55 57.82 62.28 59.96 60.17 61.01 62.81
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 88.46 86.61 61.60 60.41 63.10 59.16 85.88 60.31 55.85 62.92 90.63 58.39 90.68 61.86 60.50 62.60 60.27 63.86 91.04 58.40 61.64 59.96 60.87 61.77 60.26
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.59 61.95 61.41 64.16 86.41 85.89 89.53 60.80 43.72 83.58 59.06 60.44 88.95 58.75 62.96 90.82 59.49 61.76 57.81 56.20 59.05 62.72 58.91 59.32 61.40
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 86.08 62.11 89.24 88.21 61.33 57.30 88.03 61.34 60.75 60.41 56.87 57.80 91.44 60.22 62.39 90.00 57.36 91.76 58.30 93.22 58.84 57.87 60.68 59.20 58.29
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.41 89.64 64.51 60.15 88.57 91.93 84.97 59.55 61.58 89.38 87.44 89.31 89.54 58.04 60.00 91.49 57.67 61.25 84.20 55.10 59.92 58.83 59.86 58.21 57.07
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 87.15 61.02 89.21 89.45 89.51 59.47 90.45 61.91 89.72 61.17 91.42 92.42 91.92 91.66 59.65 92.11 61.52 92.24 57.28 59.07 62.80 61.12 58.26 49.09 60.25
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 67.03 64.19 56.95 63.81 60.94 64.67 65.05 62.46 63.43 54.37 56.47 63.51 64.68 63.70 61.45 63.25 61.09 64.53 58.98 63.46 67.46 65.03 63.54 67.04 65.84
963 372 8 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 60.85 63.50 63.62 61.26 62.15 58.41 65.24 60.98 62.46 61.48 59.95 56.54 62.70 60.54 62.86 63.08 61.40 64.59 56.59 55.71 63.80 61.48 56.99 62.79 59.08
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 65.10 67.66 68.14 66.10 64.86 62.40 65.70 65.89 65.97 64.24 60.81 60.81 54.60 64.30 65.57 64.52 65.70 67.77 60.74 61.45 64.57 64.24 60.94 64.34 62.28
975 372 8 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 63.33 62.80 61.79 64.95 65.84 59.80 55.52 60.82 64.90 61.96 60.72 58.82 58.24 60.20 61.61 64.52 62.89 62.43 58.23 57.86 64.64 62.46 62.56 62.69 67.06
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 64.52 61.93 74.37 61.89 63.27 59.53 88.48 60.54 60.39 62.14 59.26 56.64 78.46 89.22 64.01 85.55 59.32 89.74 60.38 56.91 66.98 64.43 59.66 58.94 61.59
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 64.88 61.51 86.76 60.04 65.18 90.99 87.70 60.12 61.58 43.72 90.08 91.36 61.08 85.45 58.94 56.47 61.12 59.12 90.94 56.10 61.38 60.35 61.98 55.09 61.57
1036 372 8 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 78.76 61.66 59.88 59.91 60.57 56.95 86.51 61.37 43.72 54.43 54.77 58.23 58.89 58.31 59.37 91.86 54.84 91.14 56.93 57.51 58.83 61.79 60.32 59.93 57.49
1039 372 8 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 55.62 63.66 87.85 61.11 87.49 59.58 62.96 58.74 61.71 62.46 58.36 57.84 62.81 62.08 58.59 88.74 60.57 87.11 91.85 57.35 83.91 62.08 59.05 60.13 60.43
1088 372 8 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 89.47 61.29 88.70 61.99 62.29 59.45 56.28 60.52 90.47 43.72 59.18 59.07 90.70 91.71 43.72 62.26 43.72 61.05 59.01 58.09 58.11 60.42 59.54 61.45 60.28
1091 372 8 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.33 60.56 89.77 61.74 61.80 58.55 61.66 60.21 59.13 90.22 59.93 57.33 91.30 59.88 61.11 92.07 59.72 58.81 55.28 56.11 62.23 64.16 59.63 50.33 59.19
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 87.45 64.21 62.42 62.60 63.56 91.34 89.45 62.28 60.89 60.11 59.25 59.21 92.45 60.52 61.51 90.03 60.77 60.42 92.24 86.88 59.79 60.05 57.43 59.66 49.26
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 63.03 89.71 63.81 61.33 62.54 91.95 87.41 60.60 61.73 89.97 55.43 60.38 88.64 60.93 60.68 90.69 59.64 59.23 93.43 58.29 56.40 58.01 58.74 59.47 59.36
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 68.37 65.62 62.78 62.22 66.23 59.08 55.79 65.66 67.73 66.64 61.94 59.19 65.92 69.33 63.05 58.05 64.53 65.59 48.51 61.12 65.82 66.16 67.21 65.33 65.58
1155 372 8 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 84.07 59.17 60.58 61.11 61.11 85.43 55.73 59.37 54.57 88.88 61.75 57.39 59.28 58.89 57.25 45.64 58.46 56.28 57.90 80.36 63.41 66.53 60.01 58.10 62.74
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 68.20 62.28 67.24 63.71 64.84 62.34 57.31 65.37 66.57 65.00 61.40 60.71 65.61 62.86 65.27 64.89 65.44 80.75 61.27 58.40 62.14 64.95 66.70 68.03 68.45
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 64.74 63.62 56.51 62.24 61.92 62.08 65.69 61.39 63.12 64.24 60.56 61.79 87.10 60.02 65.89 63.95 61.63 62.28 59.09 59.26 64.43 62.57 64.12 63.12 62.98
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 63.27 61.16 63.64 63.89 63.04 59.41 87.96 62.02 60.42 60.50 88.80 57.82 90.78 60.42 61.33 62.40 62.97 62.51 84.02 88.94 65.12 61.35 62.71 66.26 62.31
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.66 88.44 62.31 61.96 60.94 91.28 87.20 63.64 89.36 62.82 86.98 90.70 56.04 60.84 61.22 84.67 59.35 61.39 59.15 59.83 63.82 61.67 61.13 63.62 59.53
1228 372 8 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 55.22 62.51 57.19 62.87 86.08 90.29 61.71 63.61 62.11 68.83 57.20 60.12 69.95 60.12 62.88 89.99 62.42 58.29 56.28 57.34 61.52 63.29 60.89 58.72 60.87
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 88.83 62.63 62.88 61.70 61.02 91.52 62.38 60.62 62.78 62.57 91.21 60.65 92.54 83.03 62.55 91.64 60.60 61.60 60.32 57.10 60.35 62.67 62.53 61.87 60.43
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 89.24 60.89 62.16 90.38 88.42 91.69 88.46 60.67 61.58 62.84 61.80 59.01 90.95 59.66 59.41 91.21 58.12 59.69 57.80 58.47 60.55 56.03 60.63 59.43 60.32
1283 372 8 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 55.38 62.48 60.66 60.26 86.25 57.11 90.22 60.94 83.33 59.57 56.40 87.88 91.58 58.22 61.16 60.05 59.09 57.29 58.02 57.66 57.78 55.95 56.51 58.19 58.06
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 88.20 61.53 88.59 60.81 61.01 85.92 61.32 59.29 90.56 91.23 86.73 57.82 83.55 58.62 59.13 59.22 57.86 90.35 87.83 56.33 58.26 57.86 55.73 57.88 57.50
1295 372 8 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 62.34 63.77 61.30 60.57 89.71 91.03 83.00 60.50 88.65 61.48 59.83 58.93 91.43 57.74 60.53 90.94 60.79 62.66 58.86 58.52 61.72 63.82 50.42 59.06 56.91
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 71.63 71.01 68.87 72.86 65.75 66.28 52.33 70.72 69.71 69.62 63.73 62.72 67.67 66.51 66.65 75.97 69.87 67.94 43.72 65.17 70.15 69.81 66.60 66.17 70.97
1347 372 8 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 58.07 63.24 61.60 63.16 63.46 61.07 57.01 60.72 64.26 63.75 62.18 58.68 88.36 61.64 62.15 57.85 59.11 59.78 60.51 58.34 63.67 61.06 53.68 67.25 62.31
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 66.02 67.08 63.26 64.44 63.59 62.18 86.68 61.56 66.04 64.95 61.64 60.61 64.28 63.33 65.01 63.63 64.21 64.56 61.17 60.41 69.03 67.75 63.79 66.70 63.47
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 65.93 63.97 62.87 65.07 66.21 56.35 55.68 65.35 87.18 64.97 60.30 60.50 56.87 64.98 63.06 63.72 63.21 64.10 61.93 59.75 66.79 68.89 62.23 64.56 65.07
1408 372 8 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 63.59 61.88 87.69 62.64 58.90 88.74 56.93 61.04 61.49 59.27 59.34 57.65 88.67 56.66 59.35 61.06 59.49 58.53 58.58 55.78 62.25 63.75 61.14 59.60 60.00
1411 372 8 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 61.10 55.95 62.91 59.22 88.45 58.34 89.03 59.84 57.65 60.83 90.90 57.05 57.00 57.64 58.44 88.15 55.94 90.53 59.49 58.34 61.78 61.17 63.55 59.12 60.04
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 58.00 63.55 65.35 64.01 63.21 90.13 66.64 65.16 62.63 61.24 59.39 61.20 89.55 90.74 62.02 60.47 62.25 62.40 59.10 59.11 61.70 61.66 61.13 68.24 60.07
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 63.70 62.37 62.03 88.84 60.23 61.44 64.98 60.90 62.50 63.05 89.51 60.58 91.12 61.37 61.74 61.97 61.88 60.87 90.22 58.54 62.27 61.39 63.06 60.80 58.31
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 88.72 61.06 86.23 61.50 62.09 60.60 86.75 61.45 90.22 62.58 60.17 56.69 92.51 60.05 59.89 59.00 59.55 91.71 58.66 90.48 64.72 55.75 59.63 61.24 59.41
1475 372 8 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 87.97 61.62 87.45 60.96 60.60 59.45 62.15 59.86 61.07 89.04 91.19 59.43 91.43 60.54 60.52 58.94 60.05 58.41 58.07 56.83 57.89 59.67 56.56 57.94 59.85
1484 372 8 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 90.45 62.04 61.79 61.93 62.60 57.29 50.46 61.15 63.20 90.47 91.63 60.30 89.72 59.84 58.61 60.09 58.93 59.32 89.80 57.92 62.67 60.97 59.45 58.26 59.37
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 88.03 64.43 89.80 62.32 89.22 59.10 88.69 59.29 90.67 62.82 92.44 60.30 60.73 60.90 60.02 45.81 61.15 90.98 59.98 56.88 89.43 58.24 57.67 58.24 59.04
1536 372 8 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 45.90 62.74 63.31 64.01 62.49 61.12 49.74 62.45 65.04 64.93 62.31 43.72 60.54 62.21 55.07 63.25 65.39 55.12 59.40 56.89 68.98 64.88 65.44 66.11 62.47
1539 372 8 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 56.65 59.32 64.89 60.21 57.16 58.65 85.78 57.84 54.91 62.56 61.25 55.98 87.48 59.37 63.87 58.49 64.04 62.25 57.20 56.59 62.75 61.68 62.46 61.81 59.12
1548 372 8 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 64.36 63.75 65.04 62.51 66.83 57.21 68.48 61.14 57.22 86.28 54.98 61.65 63.35 63.08 60.73 60.74 60.08 55.55 59.00 56.52 62.88 60.27 63.02 66.89 60.30
1551 372 8 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 63.94 63.91 65.35 64.44 65.63 57.81 57.62 63.63 62.75 63.93 56.62 59.54 58.04 62.17 63.52 55.58 60.75 64.70 59.23 61.39 65.80 65.90 64.83 67.85 59.94


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
0 372 8 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 60.67 60.61 60.79 60.07 53.06 59.07 59.40 59.32 63.04 60.85 60.50 58.46 64.07 63.01 60.38 63.55 61.48 59.86 58.86 59.20 61.20 62.71 62.66 61.76 59.99
3 372 8 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 49.82 58.05 59.20 59.52 59.48 60.40 61.02 60.01 60.38 60.51 58.43 58.40 61.05 49.93 59.66 48.12 59.87 61.90 60.19 57.58 61.27 61.74 63.03 61.42 62.59
12 372 8 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 50.55 48.12 60.23 58.59 58.13 60.20 48.55 60.57 60.72 51.82 48.12 60.85 60.53 60.21 59.02 60.73 61.01 58.83 60.80 57.28 62.23 48.12 61.35 60.79 62.25
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 60.25 58.63 60.50 60.99 59.26 60.35 49.61 48.88 60.44 60.66 60.22 58.65 61.05 58.78 59.94 59.15 60.67 59.97 59.96 59.63 61.82 61.43 61.69 61.15 60.55
64 372 8 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 50.78 48.12 57.82 61.53 61.00 49.33 58.06 59.80 60.24 59.88 60.02 61.66 58.83 49.70 58.85 60.11 60.15 61.06 58.25 58.00 60.35 61.02 62.15 62.04 62.87
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 56.71 61.84 57.16 60.92 61.08 48.12 63.11 60.06 58.39 60.61 55.46 61.22 60.51 60.12 59.90 57.68 59.59 57.67 58.96 59.85 61.95 61.83 63.12 62.88 61.44
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 60.95 59.58 61.08 57.94 60.60 59.52 57.26 59.78 48.12 56.81 62.29 58.54 85.89 60.97 60.67 57.43 60.06 59.56 49.26 59.33 61.27 62.52 63.39 61.86 61.22
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 59.05 61.76 55.83 60.60 60.28 58.98 59.89 60.55 57.15 60.13 59.88 62.70 87.16 60.16 48.12 60.31 59.74 60.08 60.77 61.29 60.92 62.25 62.69 62.20 61.64
128 372 8 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 61.88 62.45 60.22 61.65 60.20 57.75 60.84 61.90 59.22 61.99 61.31 60.40 58.05 61.07 60.96 59.58 61.17 60.93 60.82 60.90 61.49 61.72 63.19 62.19 62.76
131 372 8 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 59.62 62.50 58.23 60.72 60.37 60.86 57.79 51.38 50.14 50.00 60.77 61.65 59.63 61.84 60.99 60.85 60.72 57.88 61.31 51.06 62.44 61.83 62.34 62.18 62.40
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 59.00 61.40 61.28 60.90 59.80 59.80 59.23 60.69 60.77 82.94 49.59 60.17 59.73 61.43 61.99 48.48 58.81 61.99 61.25 61.42 61.60 61.82 59.47 61.39 62.45
143 372 8 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 62.11 61.81 61.81 59.12 61.64 62.18 58.41 60.93 60.67 61.46 59.77 61.99 58.89 60.88 60.88 50.57 60.78 58.52 48.12 61.93 62.49 62.34 61.89 62.37 61.79
192 372 8 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 48.93 60.53 49.93 60.43 60.34 58.38 50.99 61.58 49.42 61.16 57.98 57.89 51.34 59.12 59.50 59.69 60.00 59.88 59.57 57.74 60.99 63.38 62.04 60.92 59.58
195 372 8 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 57.95 58.84 59.09 58.37 56.72 58.61 56.48 58.82 58.88 58.48 59.29 58.43 57.53 57.36 58.69 58.17 56.16 59.31 58.76 58.63 61.45 62.23 60.60 60.71 61.63
204 372 8 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 60.32 48.70 60.91 59.44 61.07 60.99 48.12 60.10 59.17 60.47 50.65 48.12 49.65 57.20 61.02 48.12 60.61 59.66 59.73 58.80 60.99 64.15 62.29 61.29 60.83
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 60.28 60.82 59.19 60.77 60.90 60.16 59.94 61.04 60.33 60.56 60.48 60.03 60.91 61.07 60.33 57.46 58.94 60.43 60.18 59.77 61.13 59.88 60.71 61.06 60.09
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 57.17 61.06 58.92 61.99 60.47 60.84 58.17 62.50 60.99 58.02 62.78 59.25 57.89 60.58 60.95 59.02 60.57 50.47 60.48 59.35 61.95 62.78 62.90 63.48 62.10
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 61.16 60.37 61.35 60.33 61.22 58.91 57.47 61.67 57.69 59.51 57.43 61.43 61.07 49.19 61.04 75.37 59.66 61.18 60.09 59.57 61.78 62.14 61.94 45.10 61.96
268 372 8 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 49.76 60.67 50.25 59.93 59.04 59.75 48.12 61.40 61.53 60.03 57.61 59.74 58.83 60.48 60.79 59.37 61.01 60.72 59.99 58.39 61.25 60.38 61.74 62.05 60.74
271 372 8 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 56.15 60.80 61.73 58.90 58.42 57.76 48.12 59.86 61.02 58.63 59.31 61.15 57.62 60.68 60.34 57.59 60.75 62.30 59.20 61.25 62.19 62.17 61.60 61.72 60.55
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 58.01 61.29 61.62 61.59 60.77 60.06 56.64 61.70 58.40 61.11 61.19 48.12 58.59 60.72 60.79 58.74 60.57 58.51 61.65 61.36 61.92 61.68 62.40 62.50 62.12
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 57.83 61.81 59.17 61.87 60.13 56.22 58.72 62.00 60.51 60.54 61.59 61.65 59.34 60.08 61.59 59.51 60.88 57.91 58.61 60.58 61.90 62.40 61.64 61.73 61.84
332 372 8 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 61.32 61.59 61.28 61.59 50.26 62.32 58.89 59.82 92.17 60.55 60.77 59.80 50.64 61.94 60.77 60.50 61.93 58.51 60.77 61.98 62.43 62.48 61.53 62.87 62.68
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 57.96 60.93 61.17 61.87 59.53 60.65 58.88 62.13 58.08 58.25 61.59 61.25 85.74 61.29 60.59 59.02 60.02 50.06 60.74 59.62 61.72 61.51 63.02 61.99 61.76
384 372 8 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 48.12 58.35 60.24 60.16 58.92 59.13 57.33 59.19 59.99 59.18 59.21 59.24 60.57 53.04 59.25 60.43 60.45 62.22 54.59 58.98 62.24 61.99 62.01 63.69 61.68
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 60.28 60.99 49.50 59.37 50.77 48.12 49.53 34.94 60.22 60.52 59.73 59.64 57.88 59.10 60.57 62.90 59.64 59.94 58.51 59.68 61.56 60.80 60.91 60.38 62.57
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 59.09 60.24 61.49 60.70 59.90 48.56 50.43 59.64 58.99 59.19 58.53 59.02 46.16 59.23 59.32 58.50 60.31 60.21 58.66 58.28 61.41 62.22 61.58 60.97 61.89
399 372 8 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 55.86 58.70 58.98 49.98 61.71 48.76 48.08 51.65 57.46 58.75 59.64 59.71 57.37 60.54 60.53 59.20 57.84 56.23 50.08 58.70 60.87 60.70 61.82 61.25 61.23
448 372 8 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 49.74 60.73 59.18 59.49 60.95 58.26 57.41 61.39 59.76 58.22 57.78 60.47 57.69 60.39 60.02 57.40 60.77 61.26 60.48 59.54 62.63 60.89 61.77 62.06 61.07
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 57.49 60.49 60.37 61.25 57.13 60.99 59.19 59.88 60.64 60.85 60.94 60.77 57.44 60.33 60.83 50.25 60.55 57.60 59.32 51.34 61.52 59.81 61.80 61.51 62.18
460 372 8 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 61.24 60.14 66.53 62.06 61.15 60.17 59.28 60.46 60.77 61.35 60.09 60.33 58.07 60.76 60.17 49.26 59.84 58.92 61.99 60.66 61.79 60.20 62.55 62.67 61.81
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 57.99 60.64 60.62 62.36 60.89 58.77 57.33 60.08 58.88 60.71 61.62 58.59 48.12 59.63 60.71 59.56 61.02 60.08 61.37 59.38 62.26 62.76 60.03 62.20 61.50
512 372 8 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 57.85 58.74 61.53 61.64 61.40 58.30 61.26 61.53 60.07 60.74 61.59 61.18 48.12 60.75 60.93 85.97 60.97 61.11 61.31 61.41 63.03 61.69 61.39 62.29 61.43
515 372 8 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 61.23 61.66 49.59 61.66 61.16 59.90 57.99 61.70 58.21 60.99 62.70 50.25 50.54 60.47 62.00 50.65 60.64 61.39 61.37 59.62 61.63 61.85 62.67 63.04 61.99
524 372 8 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 56.61 60.61 61.38 61.71 61.18 56.17 58.35 61.65 59.67 61.29 58.86 59.92 61.45 61.22 61.36 76.02 60.98 58.99 59.67 59.90 62.24 62.15 61.83 61.67 60.93
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 59.57 61.65 61.75 61.97 61.93 60.21 57.26 61.17 59.84 90.67 61.59 61.84 59.60 62.08 61.88 50.58 60.67 62.08 61.56 60.65 60.46 62.85 62.18 62.57 62.59
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 60.45 61.30 59.49 60.16 61.74 60.65 47.99 59.83 59.84 59.66 58.99 59.42 59.25 65.80 60.63 57.96 59.14 58.87 59.85 59.29 61.48 60.29 60.60 61.10 60.83
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 48.54 60.64 59.58 61.28 59.33 60.09 59.38 60.90 49.46 61.36 60.48 59.51 61.29 59.35 59.93 58.57 60.40 59.43 60.17 59.24 60.95 61.78 60.88 60.48 61.94
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 56.41 61.73 59.97 59.28 58.14 59.05 60.52 59.74 58.57 59.96 59.29 61.46 59.41 59.37 60.99 60.52 59.27 59.80 60.03 58.47 60.92 62.67 62.42 62.53 62.51
591 372 8 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 59.49 59.41 59.55 60.24 59.07 48.12 48.39 58.98 60.07 59.18 61.13 58.90 61.37 59.84 58.91 61.47 50.34 59.79 60.61 60.54 61.86 48.12 48.12 62.06 62.20
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 57.99 60.21 59.58 61.00 57.73 60.33 58.21 59.95 61.74 58.42 59.64 58.78 58.51 60.82 60.46 59.90 60.54 60.27 59.71 60.40 61.68 62.03 62.78 61.74 61.32
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 61.36 60.61 61.13 61.09 61.63 59.73 58.49 61.39 48.12 61.11 60.42 60.58 60.42 60.41 59.95 57.77 60.18 82.74 60.06 60.70 60.98 61.74 61.66 62.07 60.83
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 56.37 61.66 60.05 61.79 59.96 57.62 56.24 61.40 58.62 61.16 59.15 61.47 58.97 60.51 61.25 60.77 60.48 60.63 61.58 59.21 62.44 61.45 61.79 61.67 61.68
655 372 8 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 60.40 62.42 61.22 62.00 61.47 48.12 61.49 60.20 61.09 61.03 61.52 61.65 57.44 60.59 61.80 60.65 60.10 59.48 60.04 61.15 61.62 61.27 60.53 62.37 61.60
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 61.16 61.87 61.27 59.81 61.81 60.11 59.64 61.76 60.67 61.39 60.33 62.39 59.28 60.90 61.75 59.43 61.49 59.45 62.97 59.04 60.33 62.55 62.20 62.42 61.84
707 372 8 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 60.22 60.66 61.89 61.29 57.85 61.99 59.09 62.22 48.88 62.32 60.77 61.77 59.21 61.36 61.48 59.67 60.88 61.75 61.47 61.81 62.45 62.79 62.81 62.54 62.19
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 59.31 61.99 61.92 48.12 59.52 60.33 57.82 61.82 49.18 58.63 61.99 61.99 59.42 61.82 60.75 51.35 61.10 60.51 61.65 58.84 59.87 62.26 61.49 62.49 61.77
719 372 8 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 61.05 59.74 50.01 61.03 59.41 60.41 58.25 60.55 59.85 61.37 49.75 61.99 59.20 60.18 61.50 60.74 60.85 59.52 61.64 88.98 62.50 62.36 61.50 62.01 61.18
768 372 8 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 58.39 60.70 59.18 58.28 50.71 59.58 50.84 48.12 58.12 61.11 58.42 58.52 48.12 61.08 59.95 59.86 66.08 62.36 57.38 57.74 61.19 62.29 61.48 62.89 62.60
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 60.37 60.53 59.30 59.82 59.35 59.11 58.86 59.02 59.90 58.47 60.42 58.41 57.62 59.61 60.41 59.59 59.15 58.18 58.40 58.78 61.00 62.25 62.75 61.69 61.80
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 60.00 61.22 59.12 59.67 58.37 58.81 50.37 61.32 59.24 60.53 60.17 59.41 60.04 59.35 60.91 59.38 59.46 59.86 59.17 59.99 62.31 60.74 61.62 61.28 62.22
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 60.56 59.71 59.33 60.97 60.61 59.52 60.07 60.49 58.70 60.13 59.75 59.84 59.18 60.14 59.75 60.20 58.81 59.11 58.85 58.62 60.71 61.40 60.08 61.70 60.09
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 60.48 61.67 58.67 59.36 61.23 60.98 58.96 60.32 53.08 61.16 47.75 61.53 60.64 60.57 60.71 59.77 60.35 60.99 62.28 58.05 61.06 62.44 62.17 61.79 62.48
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 58.08 61.37 58.96 58.38 60.80 61.85 58.29 89.01 56.62 61.50 58.78 59.20 58.43 60.99 60.38 59.68 60.16 59.31 60.31 60.53 61.24 62.19 62.16 61.55 60.72
844 372 8 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 49.44 60.31 50.47 59.82 60.71 59.42 47.21 61.57 61.39 60.81 58.51 59.61 57.42 61.12 60.53 56.01 57.28 61.29 61.66 60.56 61.87 60.21 62.32 61.67 61.06
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 58.93 57.38 60.72 58.88 60.38 60.76 56.88 61.05 48.85 61.35 59.16 60.53 58.76 60.47 60.43 59.71 59.80 61.07 58.03 60.54 62.28 60.86 60.80 61.32 60.97
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 58.90 61.42 61.01 61.89 59.72 90.60 57.93 61.16 48.12 49.42 61.53 60.11 57.97 61.67 61.07 59.29 62.18 61.67 61.25 59.62 61.79 62.34 62.00 62.89 62.17
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 55.59 61.42 59.07 59.73 61.53 59.14 59.76 62.11 62.00 60.96 59.71 61.04 59.04 61.46 62.16 57.13 61.68 58.35 61.65 59.00 60.92 62.45 62.07 62.63 62.41
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 57.80 59.56 61.33 60.44 58.48 59.95 51.41 62.00 61.36 59.18 51.55 51.81 60.01 61.70 62.25 59.72 61.00 61.46 87.31 59.06 61.43 61.60 61.15 62.61 62.49
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.59 62.00 59.07 59.52 59.22 61.90 59.49 60.91 59.71 62.32 60.22 59.95 59.59 58.21 62.28 59.05 60.03 59.22 62.90 60.65 61.57 62.42 62.09 48.62 62.01
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 60.48 58.84 49.00 61.14 60.04 60.17 61.04 58.86 60.07 50.20 50.66 60.31 58.74 60.01 59.48 59.73 62.43 58.82 59.54 59.23 61.64 62.09 62.32 67.02 61.17
963 372 8 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 59.83 61.15 59.44 60.53 58.33 58.73 59.53 58.36 57.54 60.46 59.76 60.96 60.62 59.45 59.28 59.53 58.27 59.73 59.78 59.01 60.52 58.70 60.99 62.26 61.56
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 59.24 59.36 60.97 61.00 60.42 59.84 61.00 64.43 60.39 59.34 59.26 59.12 52.63 59.28 61.40 58.31 59.07 58.26 60.52 60.05 61.14 61.89 62.95 60.19 61.50
975 372 8 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 59.51 59.23 58.49 59.84 60.77 58.76 49.29 59.67 58.20 58.83 60.22 58.62 48.01 59.47 59.33 60.43 62.39 59.73 58.66 59.10 61.94 61.43 61.83 62.20 60.55
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 61.27 61.25 52.36 59.48 61.44 62.71 57.80 59.08 60.15 60.77 60.37 50.57 47.44 58.54 57.87 50.54 58.64 56.67 60.82 58.25 61.46 60.99 62.49 62.74 61.97
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 60.53 59.99 58.64 60.24 60.74 59.67 58.80 59.26 58.73 48.12 50.01 59.15 59.59 47.94 60.59 49.59 60.45 60.70 58.70 59.60 60.63 62.15 60.19 62.50 61.08
1036 372 8 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.56 60.87 60.22 60.96 58.87 58.74 50.02 59.07 48.12 63.17 51.59 60.22 59.64 61.28 60.48 57.85 50.78 56.76 60.44 60.06 61.60 62.23 61.82 62.20 60.54
1039 372 8 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 50.29 61.89 57.17 60.76 57.43 61.04 60.65 60.24 60.21 60.19 59.18 60.79 59.52 60.47 61.51 57.43 60.94 85.19 58.88 60.60 85.64 62.23 62.47 61.80 61.80
1088 372 8 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 58.72 60.17 59.06 61.71 61.64 61.61 49.90 61.99 58.61 48.12 61.99 61.75 58.92 60.02 48.12 61.46 48.12 61.75 61.99 60.81 62.48 61.92 62.45 62.43 61.15
1091 372 8 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 58.45 59.52 58.63 60.77 62.06 60.59 61.26 61.05 61.14 58.85 62.39 61.31 58.87 60.85 61.91 58.48 61.09 61.40 50.00 59.57 60.04 61.91 61.03 50.48 62.19
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.69 61.55 61.21 61.31 60.72 59.48 59.22 61.70 61.51 61.44 61.87 61.58 59.52 61.48 61.70 57.64 60.82 62.09 59.37 52.38 62.90 62.33 62.28 62.56 46.25
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 61.88 59.48 61.29 60.75 61.99 58.62 59.27 61.15 61.02 59.12 59.17 61.99 60.19 60.59 60.40 59.37 61.36 60.98 59.95 61.87 62.48 62.69 62.56 62.08 62.25
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 60.37 59.61 62.79 61.30 60.04 58.65 48.61 60.23 60.99 61.33 59.69 59.64 61.55 58.70 61.14 64.98 60.01 59.73 45.95 58.82 61.66 60.99 61.35 61.42 61.67
1155 372 8 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 55.41 60.20 59.56 60.05 60.82 56.21 50.23 58.47 50.55 57.07 59.69 58.91 61.46 59.56 59.04 44.10 59.55 49.20 59.70 82.65 61.67 60.51 62.71 62.61 59.08
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 60.29 59.06 60.26 59.11 58.96 59.30 49.40 59.95 57.95 58.74 60.44 59.07 61.23 61.30 59.04 59.70 60.46 59.21 60.62 57.95 62.32 59.21 62.06 60.46 61.03
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 59.77 60.61 50.31 61.56 60.59 59.52 61.64 59.37 61.15 60.78 60.79 59.54 58.83 59.18 61.36 59.91 60.02 59.35 59.66 59.65 60.04 61.29 61.47 61.44 61.43
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 60.29 58.88 58.27 59.47 60.96 58.90 58.23 59.86 58.78 60.37 51.23 59.47 58.42 58.87 59.18 61.58 60.81 62.28 87.45 56.55 61.40 61.39 61.63 61.38 61.64
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 58.28 59.36 61.75 60.33 60.39 59.30 58.88 61.50 58.12 61.65 50.92 59.48 50.25 60.22 61.29 52.21 60.78 59.76 59.47 61.65 61.61 62.72 61.79 61.42 61.71
1228 372 8 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 50.68 60.37 49.94 61.59 55.85 59.35 59.72 62.02 58.91 75.73 59.57 60.83 45.60 60.14 60.46 58.86 59.30 60.66 50.32 60.08 61.04 62.18 62.88 61.84 62.40
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 58.67 60.27 60.46 61.03 59.32 60.02 61.50 61.64 59.92 61.77 59.33 61.59 59.18 86.26 59.51 59.70 60.43 61.45 61.53 59.63 63.13 61.59 62.18 61.63 62.10
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 59.53 61.03 61.48 60.14 59.80 59.61 59.30 62.09 60.34 61.14 61.59 61.99 59.28 61.18 60.86 58.80 60.32 61.80 60.11 61.12 63.47 62.84 62.55 62.18 61.89
1283 372 8 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 50.30 60.97 60.71 61.29 58.25 59.37 59.32 61.70 87.38 61.66 60.97 50.82 59.55 61.47 61.93 61.64 60.74 60.09 62.17 61.94 62.08 62.60 62.08 61.61 60.91
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 59.39 61.99 58.51 61.33 61.43 51.96 59.62 61.93 58.49 58.87 86.78 61.70 49.68 60.50 60.58 61.39 59.97 59.52 50.60 61.87 62.20 62.13 62.58 62.33 61.14
1295 372 8 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 61.10 60.69 61.93 61.81 59.71 58.52 90.79 61.70 58.97 62.08 60.65 61.49 59.23 62.39 60.97 59.27 60.04 60.14 62.64 61.68 61.42 61.55 49.99 61.84 62.18
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 58.91 58.94 61.11 58.72 61.35 56.96 50.01 59.52 59.68 60.07 58.32 57.76 60.52 60.60 61.13 61.70 59.03 61.34 48.12 57.87 59.88 60.80 61.63 61.83 62.05
1347 372 8 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 47.82 61.17 59.82 59.57 60.34 59.40 49.53 60.21 60.47 59.85 61.06 57.91 57.64 60.18 60.69 51.20 59.20 62.34 60.38 50.44 62.57 62.78 43.86 59.36 62.42
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 59.76 60.13 60.05 60.35 60.05 59.96 57.98 59.20 60.40 60.34 62.12 59.63 59.23 59.66 60.04 60.79 59.02 58.91 60.55 59.14 60.72 60.68 61.87 60.69 61.55
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 59.03 61.01 60.33 60.32 61.74 49.79 49.14 59.19 56.83 59.25 62.16 60.12 49.87 59.80 59.64 60.08 59.62 59.50 59.18 59.86 59.54 59.35 61.98 61.48 61.16
1408 372 8 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 61.11 60.40 57.03 60.92 60.10 56.97 49.51 60.34 60.39 61.21 59.43 59.66 58.03 50.16 59.89 60.37 61.39 62.21 60.96 50.31 61.75 61.65 62.56 61.71 62.00
1411 372 8 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 59.34 49.49 59.98 59.43 59.49 60.58 58.35 61.24 58.61 59.85 56.87 60.20 50.35 59.94 58.70 57.54 50.11 57.48 61.77 60.65 61.76 61.25 60.71 60.97 61.43
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 50.11 61.27 58.98 61.63 60.02 58.25 59.78 61.15 60.09 59.62 62.13 61.93 58.32 59.24 60.30 59.93 60.67 60.68 61.03 60.19 61.77 62.31 62.36 60.26 62.08
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 61.92 61.03 61.37 57.93 60.93 61.45 60.20 60.77 61.42 61.28 55.55 61.59 58.63 61.33 60.50 60.24 60.29 60.38 57.35 61.53 60.75 62.25 62.11 61.45 61.00
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 58.88 62.32 56.32 60.97 61.41 60.92 88.18 61.11 57.61 60.48 62.32 59.93 58.31 62.18 61.58 60.71 60.72 58.94 60.46 50.61 60.25 49.51 62.36 62.52 61.00
1475 372 8 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 59.15 61.47 59.52 61.06 61.29 61.68 61.33 61.11 61.59 58.82 59.95 62.26 59.33 62.15 61.94 61.23 61.26 59.76 61.16 61.59 62.42 61.83 62.55 61.26 62.11
1484 372 8 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 59.32 59.92 61.75 60.41 61.02 49.75 51.94 61.93 61.51 59.39 57.41 61.65 59.15 61.21 60.51 58.17 60.23 60.93 52.20 60.44 61.80 62.36 61.79 61.53 62.39
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.74 61.52 59.26 62.32 59.41 62.08 58.77 61.93 59.10 61.42 59.79 62.15 62.16 61.21 61.42 65.45 60.75 59.48 61.53 59.45 60.03 60.47 61.95 61.82 62.28
1536 372 8 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 65.84 60.24 60.10 59.36 60.05 59.22 52.83 61.08 60.87 58.17 60.09 48.12 61.69 59.97 51.91 59.40 59.82 49.84 59.64 58.52 60.46 61.24 61.34 61.46 60.41
1539 372 8 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 50.63 58.35 60.87 58.59 49.01 60.10 56.52 58.89 50.75 59.44 58.07 59.70 57.61 60.23 60.41 57.36 59.25 59.84 59.32 58.67 61.77 60.74 62.07 62.18 61.88
1548 372 8 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 59.36 59.74 59.79 59.97 60.43 59.43 60.07 59.30 49.35 56.92 51.45 61.13 59.62 58.60 62.08 61.55 57.92 50.00 59.68 50.13 63.10 62.31 62.37 60.38 62.83
1551 372 8 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 60.89 60.25 58.80 60.59 60.03 57.87 49.64 59.64 59.02 59.01 49.99 60.37 49.19 61.63 60.34 51.26 60.23 59.44 59.77 60.04 61.33 61.10 61.75 60.55 62.46
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.66 88.44 62.31 61.96 60.94 91.28 87.20 63.64 89.36 62.82 86.98 90.70 56.04 60.84 61.22 84.67 59.35 61.39 59.15 59.83 63.82 61.67 61.13 63.62 59.53
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 88.83 62.63 62.88 61.70 61.02 91.52 62.38 60.62 62.78 62.57 91.21 60.65 92.54 83.03 62.55 91.64 60.60 61.60 60.32 57.10 60.35 62.67 62.53 61.87 60.43
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 87.47 62.41 89.51 89.18 63.55 61.14 89.94 83.67 86.95 61.73 91.83 56.81 90.30 60.45 58.77 61.30 59.06 58.12 56.86 58.99 60.80 58.11 60.52 59.49 57.66
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 64.88 61.51 86.76 60.04 65.18 90.99 87.70 60.12 61.58 43.72 90.08 91.36 61.08 85.45 58.94 56.47 61.12 59.12 90.94 56.10 61.38 60.35 61.98 55.09 61.57
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 86.26 62.62 86.84 61.63 60.48 43.72 57.24 61.21 87.21 64.21 88.46 59.04 61.32 58.84 59.32 90.48 61.27 88.08 92.21 56.29 60.43 60.39 59.65 59.73 59.58
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 64.71 60.70 62.10 87.85 61.14 91.88 88.30 59.57 43.72 87.16 59.27 92.18 84.02 59.93 61.20 88.62 60.33 59.00 90.56 55.89 59.57 60.94 56.45 60.44 61.52
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 88.57 62.53 86.74 61.84 61.35 92.60 88.93 61.47 89.55 62.20 92.17 59.70 84.94 62.20 43.72 60.71 59.85 61.03 59.30 58.30 64.25 62.34 59.50 62.20 58.68
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.22 64.25 87.63 63.04 63.92 60.11 88.64 62.74 64.17 87.34 60.43 57.99 87.00 61.27 64.76 92.24 59.90 56.52 59.80 92.46 59.68 60.61 61.01 57.17 59.93
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 88.14 62.84 61.63 60.46 88.38 58.93 89.46 88.86 61.80 61.29 59.60 58.61 89.41 59.21 61.06 55.82 59.76 89.98 58.68 87.52 63.16 61.20 60.36 58.98 60.35
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 89.24 60.89 62.16 90.38 88.42 91.69 88.46 60.67 61.58 62.84 61.80 59.01 90.95 59.66 59.41 91.21 58.12 59.69 57.80 58.47 60.55 56.03 60.63 59.43 60.32
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 88.20 61.53 88.59 60.81 61.01 85.92 61.32 59.29 90.56 91.23 86.73 57.82 83.55 58.62 59.13 59.22 57.86 90.35 87.83 56.33 58.26 57.86 55.73 57.88 57.50
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 88.72 61.06 86.23 61.50 62.09 60.60 86.75 61.45 90.22 62.58 60.17 56.69 92.51 60.05 59.89 59.00 59.55 91.71 58.66 90.48 64.72 55.75 59.63 61.24 59.41
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 88.03 64.43 89.80 62.32 89.22 59.10 88.69 59.29 90.67 62.82 92.44 60.30 60.73 60.90 60.02 45.81 61.15 90.98 59.98 56.88 89.43 58.24 57.67 58.24 59.04
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 65.25 62.53 62.98 88.91 63.72 59.18 66.74 61.76 63.52 64.78 91.15 60.24 91.00 61.57 61.56 91.71 61.03 90.47 57.54 91.96 65.10 58.98 60.12 58.59 65.50
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 88.62 62.81 63.61 43.72 88.97 90.42 87.91 60.78 85.04 89.48 60.52 57.91 89.44 57.22 59.08 86.23 59.34 60.60 57.05 92.21 87.43 58.46 58.25 60.01 59.03
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.59 61.95 61.41 64.16 86.41 85.89 89.53 60.80 43.72 83.58 59.06 60.44 88.95 58.75 62.96 90.82 59.49 61.76 57.81 56.20 59.05 62.72 58.91 59.32 61.40
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 86.08 62.11 89.24 88.21 61.33 57.30 88.03 61.34 60.75 60.41 56.87 57.80 91.44 60.22 62.39 90.00 57.36 91.76 58.30 93.22 58.84 57.87 60.68 59.20 58.29
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.41 89.64 64.51 60.15 88.57 91.93 84.97 59.55 61.58 89.38 87.44 89.31 89.54 58.04 60.00 91.49 57.67 61.25 84.20 55.10 59.92 58.83 59.86 58.21 57.07
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 87.15 61.02 89.21 89.45 89.51 59.47 90.45 61.91 89.72 61.17 91.42 92.42 91.92 91.66 59.65 92.11 61.52 92.24 57.28 59.07 62.80 61.12 58.26 49.09 60.25
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 87.45 64.21 62.42 62.60 63.56 91.34 89.45 62.28 60.89 60.11 59.25 59.21 92.45 60.52 61.51 90.03 60.77 60.42 92.24 86.88 59.79 60.05 57.43 59.66 49.26
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 63.03 89.71 63.81 61.33 62.54 91.95 87.41 60.60 61.73 89.97 55.43 60.38 88.64 60.93 60.68 90.69 59.64 59.23 93.43 58.29 56.40 58.01 58.74 59.47 59.36
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 89.47 61.30 61.12 62.20 87.85 90.42 89.08 61.95 60.60 82.15 89.54 57.66 91.40 60.55 61.03 88.85 92.48 60.05 58.38 58.68 57.06 62.07 90.09 59.18 57.38
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 88.35 61.48 86.23 60.74 59.33 90.19 90.24 59.94 60.55 61.32 59.04 56.87 88.98 58.24 58.85 59.08 59.01 91.17 93.15 56.00 59.11 58.23 59.09 60.54 60.49
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 88.57 60.13 60.22 61.27 89.95 58.07 90.81 60.70 90.41 90.49 58.59 60.34 82.30 57.75 60.22 91.60 60.09 55.97 57.90 55.78 59.52 61.56 56.52 58.71 59.57
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 88.01 62.31 62.86 62.19 62.80 59.34 88.41 61.60 91.55 85.37 61.19 59.33 90.96 60.55 60.55 88.35 59.50 60.20 59.18 58.00 88.72 58.71 59.77 59.87 56.81
Size of the All data:  (100, 28)
Size of the Sig data:  (25, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
4 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 58.28 59.36 61.75 60.33 60.39 59.30 58.88 61.50 58.12 61.65 50.92 59.48 50.25 60.22 61.29 52.21 60.78 59.76 59.47 61.65 61.61 62.72 61.79 61.42 61.71
17 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 58.67 60.27 60.46 61.03 59.32 60.02 61.50 61.64 59.92 61.77 59.33 61.59 59.18 86.26 59.51 59.70 60.43 61.45 61.53 59.63 63.13 61.59 62.18 61.63 62.10
9 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 58.08 61.37 58.96 58.38 60.80 61.85 58.29 89.01 56.62 61.50 58.78 59.20 58.43 60.99 60.38 59.68 60.16 59.31 60.31 60.53 61.24 62.19 62.16 61.55 60.72
21 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 60.53 59.99 58.64 60.24 60.74 59.67 58.80 59.26 58.73 48.12 50.01 59.15 59.59 47.94 60.59 49.59 60.45 60.70 58.70 59.60 60.63 62.15 60.19 62.50 61.08
23 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 56.71 61.84 57.16 60.92 61.08 48.12 63.11 60.06 58.39 60.61 55.46 61.22 60.51 60.12 59.90 57.68 59.59 57.67 58.96 59.85 61.95 61.83 63.12 62.88 61.44
11 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 60.95 59.58 61.08 57.94 60.60 59.52 57.26 59.78 48.12 56.81 62.29 58.54 85.89 60.97 60.67 57.43 60.06 59.56 49.26 59.33 61.27 62.52 63.39 61.86 61.22
19 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 59.05 61.76 55.83 60.60 60.28 58.98 59.89 60.55 57.15 60.13 59.88 62.70 87.16 60.16 48.12 60.31 59.74 60.08 60.77 61.29 60.92 62.25 62.69 62.20 61.64
10 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 57.17 61.06 58.92 61.99 60.47 60.84 58.17 62.50 60.99 58.02 62.78 59.25 57.89 60.58 60.95 59.02 60.57 50.47 60.48 59.35 61.95 62.78 62.90 63.48 62.10
18 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 57.49 60.49 60.37 61.25 57.13 60.99 59.19 59.88 60.64 60.85 60.94 60.77 57.44 60.33 60.83 50.25 60.55 57.60 59.32 51.34 61.52 59.81 61.80 61.51 62.18
15 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 59.53 61.03 61.48 60.14 59.80 59.61 59.30 62.09 60.34 61.14 61.59 61.99 59.28 61.18 60.86 58.80 60.32 61.80 60.11 61.12 63.47 62.84 62.55 62.18 61.89
5 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 59.39 61.99 58.51 61.33 61.43 51.96 59.62 61.93 58.49 58.87 86.78 61.70 49.68 60.50 60.58 61.39 59.97 59.52 50.60 61.87 62.20 62.13 62.58 62.33 61.14
14 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 58.88 62.32 56.32 60.97 61.41 60.92 88.18 61.11 57.61 60.48 62.32 59.93 58.31 62.18 61.58 60.71 60.72 58.94 60.46 50.61 60.25 49.51 62.36 62.52 61.00
7 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.74 61.52 59.26 62.32 59.41 62.08 58.77 61.93 59.10 61.42 59.79 62.15 62.16 61.21 61.42 65.45 60.75 59.48 61.53 59.45 60.03 60.47 61.95 61.82 62.28
8 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 61.16 61.87 61.27 59.81 61.81 60.11 59.64 61.76 60.67 61.39 60.33 62.39 59.28 60.90 61.75 59.43 61.49 59.45 62.97 59.04 60.33 62.55 62.20 62.42 61.84
3 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 59.31 61.99 61.92 48.12 59.52 60.33 57.82 61.82 49.18 58.63 61.99 61.99 59.42 61.82 60.75 51.35 61.10 60.51 61.65 58.84 59.87 62.26 61.49 62.49 61.77
24 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 58.90 61.42 61.01 61.89 59.72 90.60 57.93 61.16 48.12 49.42 61.53 60.11 57.97 61.67 61.07 59.29 62.18 61.67 61.25 59.62 61.79 62.34 62.00 62.89 62.17
6 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 55.59 61.42 59.07 59.73 61.53 59.14 59.76 62.11 62.00 60.96 59.71 61.04 59.04 61.46 62.16 57.13 61.68 58.35 61.65 59.00 60.92 62.45 62.07 62.63 62.41
1 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 57.80 59.56 61.33 60.44 58.48 59.95 51.41 62.00 61.36 59.18 51.55 51.81 60.01 61.70 62.25 59.72 61.00 61.46 87.31 59.06 61.43 61.60 61.15 62.61 62.49
0 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.59 62.00 59.07 59.52 59.22 61.90 59.49 60.91 59.71 62.32 60.22 59.95 59.59 58.21 62.28 59.05 60.03 59.22 62.90 60.65 61.57 62.42 62.09 48.62 62.01
12 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.69 61.55 61.21 61.31 60.72 59.48 59.22 61.70 61.51 61.44 61.87 61.58 59.52 61.48 61.70 57.64 60.82 62.09 59.37 52.38 62.90 62.33 62.28 62.56 46.25
13 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 61.88 59.48 61.29 60.75 61.99 58.62 59.27 61.15 61.02 59.12 59.17 61.99 60.19 60.59 60.40 59.37 61.36 60.98 59.95 61.87 62.48 62.69 62.56 62.08 62.25
2 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 59.00 61.40 61.28 60.90 59.80 59.80 59.23 60.69 60.77 82.94 49.59 60.17 59.73 61.43 61.99 48.48 58.81 61.99 61.25 61.42 61.60 61.82 59.47 61.39 62.45
20 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 57.83 61.81 59.17 61.87 60.13 56.22 58.72 62.00 60.51 60.54 61.59 61.65 59.34 60.08 61.59 59.51 60.88 57.91 58.61 60.58 61.90 62.40 61.64 61.73 61.84
22 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 57.96 60.93 61.17 61.87 59.53 60.65 58.88 62.13 58.08 58.25 61.59 61.25 85.74 61.29 60.59 59.02 60.02 50.06 60.74 59.62 61.72 61.51 63.02 61.99 61.76
16 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 59.57 61.65 61.75 61.97 61.93 60.21 57.26 61.17 59.84 90.67 61.59 61.84 59.60 62.08 61.88 50.58 60.67 62.08 61.56 60.65 60.46 62.85 62.18 62.57 62.59
Size of the test data:  (25, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.38 -29.08 -0.56 -1.63 -0.55 -31.98 -28.32 -2.14 -31.24 -1.17 -36.06 -31.22 -5.79 -0.62 0.07 -32.46 1.43 -1.63 0.32 1.82 -2.21 1.05 0.66 -2.20 2.18 18
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.35 -1.52 -28.12 0.20 -4.44 -31.32 -28.90 -0.86 -2.85 4.40 -40.07 -32.21 -1.49 -37.51 1.65 -6.88 -0.67 1.58 -32.24 3.50 -0.75 1.80 -1.79 7.41 -0.49 18
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.16 -2.36 -2.42 -0.67 -1.70 -31.50 -0.88 1.02 -2.86 -0.80 -31.88 0.94 -33.36 3.23 -3.04 -31.94 -0.17 -0.15 1.21 2.53 2.78 -1.08 -0.35 -0.24 1.67 18
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.52 -0.77 -30.91 -1.24 -1.07 -33.62 -29.04 -0.92 -32.40 -2.07 -32.29 3.00 2.22 -2.04 4.40 -0.40 -0.11 -0.95 1.47 2.99 -3.33 -0.09 3.19 -0.00 2.96 17
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.09 -0.66 -1.71 -29.10 -1.91 0.93 -7.10 -0.00 -2.85 -3.39 -30.82 2.15 -31.72 -0.67 0.19 -32.28 0.46 -31.02 5.43 -32.92 -4.77 3.57 2.08 3.83 -3.66 16
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.56 0.98 -30.14 -29.93 -30.29 2.43 -30.96 -1.00 -30.01 1.15 -31.20 -32.47 -32.33 -33.45 2.63 -33.06 -1.49 -33.02 5.62 1.58 -1.23 1.30 3.83 -0.47 1.76 16
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.05 -3.19 -28.71 -1.05 -3.45 0.73 -30.47 -0.24 -3.18 -29.32 2.35 1.26 -29.11 -0.69 -3.81 -33.22 0.67 -6.05 0.68 -33.11 2.27 2.17 1.89 6.31 2.17 15
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.65 -2.35 -1.26 0.79 -31.25 2.06 -30.27 -28.98 -1.16 -0.44 1.34 2.16 -31.97 1.12 -0.23 -5.57 0.79 -32.38 0.64 -36.18 -1.64 -1.39 1.44 2.53 1.83 15
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -3.76 -1.12 -1.02 -29.91 -0.54 -32.36 -31.04 0.21 4.40 -30.35 3.02 -33.64 1.87 1.04 -0.53 -31.19 -0.27 0.56 -41.30 3.44 1.70 1.58 6.94 1.42 -0.30 14
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.15 -30.23 -2.52 -0.58 -0.55 -33.33 -28.14 0.55 -0.71 -30.85 3.74 1.61 -28.45 -0.34 -0.28 -31.32 1.72 1.75 -33.48 3.58 6.08 4.68 3.82 2.61 2.89 14
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.76 -2.66 -1.21 -1.29 -2.84 -31.86 -30.23 -0.58 0.62 1.33 2.62 2.37 -32.93 0.96 0.19 -32.39 0.05 1.67 -32.87 -34.50 3.11 2.28 4.85 2.90 -3.01 13
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.55 -0.78 -29.68 -0.71 0.60 4.40 5.87 -1.15 -28.82 -3.60 -33.00 2.18 -0.81 1.28 0.58 -32.80 -1.68 -30.41 -33.25 3.56 1.52 1.44 3.47 3.15 1.86 13
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.31 -0.82 -1.69 4.40 -29.45 -30.09 -30.09 1.04 -35.86 -30.85 1.47 4.08 -30.02 4.60 1.67 -34.88 1.76 -0.09 4.60 -33.37 -27.56 3.80 3.24 2.48 2.74 13
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.69 -0.53 -0.40 -2.27 -26.69 4.71 -31.60 0.36 4.40 -34.16 2.47 -0.33 -30.98 2.92 -1.89 -31.53 2.69 -0.09 3.44 3.42 2.74 -0.38 3.09 3.57 0.77 13
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -32.61 -30.08 -3.18 0.29 -30.09 -31.98 -33.56 2.45 -0.22 -30.20 -35.89 -37.50 -29.53 3.66 2.25 -31.77 3.33 0.21 3.11 3.96 1.51 2.77 1.29 4.40 5.42 12
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.84 1.26 -29.91 -0.53 -0.68 0.32 1.43 -0.34 -32.61 -2.10 2.15 3.24 -34.20 2.13 1.69 1.71 1.17 -32.77 1.80 -39.87 -4.47 -6.24 2.73 1.28 1.59 12
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.47 0.10 0.16 -1.30 -28.05 -30.62 -29.85 -1.26 0.17 0.79 -39.95 2.51 -31.67 0.88 0.96 -40.37 -33.67 1.94 2.87 2.74 4.54 -0.25 -30.62 2.21 5.07 12
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.29 -2.91 -30.54 -0.00 -29.81 2.98 -29.92 2.64 -31.57 -1.40 -32.65 1.85 1.43 0.31 1.40 19.64 -0.40 -31.50 1.55 2.57 -29.40 2.23 4.28 3.58 3.24 11
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.71 0.14 -0.68 -30.24 -28.62 -32.08 -29.16 1.42 -1.24 -1.70 -0.21 2.98 -31.67 1.52 1.45 -32.41 2.20 2.11 2.31 2.65 2.92 6.81 1.92 2.75 1.57 11
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.39 -1.04 -30.55 -30.80 -2.75 0.71 -31.65 5.34 -30.33 -0.23 -33.05 2.39 -31.87 0.54 1.61 -1.62 1.10 1.19 3.45 1.54 0.44 4.08 1.64 2.06 3.06 11
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.44 -0.66 -1.11 -0.22 -0.87 0.87 -31.15 -0.43 -31.71 5.30 0.40 2.51 -31.36 1.53 1.33 -37.77 1.17 1.88 2.38 2.65 -28.26 4.14 2.41 2.70 5.78 11
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.49 -0.69 -30.17 -28.48 0.20 1.84 -28.27 0.77 1.25 0.55 2.84 3.24 -32.40 1.24 -0.23 -32.87 4.32 -33.41 3.35 -34.22 2.08 4.58 1.39 3.43 4.12 10
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.81 0.46 -30.08 0.52 0.42 -33.96 -1.70 2.64 -32.07 -32.36 0.05 3.88 -33.87 1.88 1.45 2.17 2.11 -30.83 -37.23 5.54 3.94 4.27 6.85 4.45 3.64 9
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.52 0.33 -27.06 1.13 0.80 -33.97 -31.52 2.06 -0.04 -0.78 2.55 4.78 -29.64 1.84 2.74 0.43 1.87 -33.26 -34.54 4.58 2.79 4.17 2.55 1.19 1.35 9
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.61 0.80 0.95 0.60 -30.42 2.58 -31.93 1.43 -32.33 -32.24 3.00 0.91 3.44 3.54 0.37 -32.58 -0.07 -5.91 2.84 3.84 2.20 -0.05 6.50 3.28 2.19 9

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_13 84.4564 11.376413
mAP_valid_abs_values 84.3564 8.921018
mAP_valid_abs_values_7 84.3216 10.150079
mAP_valid_abs_values_16 79.5260 15.968719
mAP_valid_abs_values_6 76.1992 16.910606
mAP_valid_abs_values_11 74.0268 15.727979
mAP_valid_abs_values_3 73.6320 12.956814
mAP_valid_abs_values_9 72.4084 16.013372
mAP_valid_abs_values_5 71.6496 13.036881
mAP_valid_abs_values_10 71.6288 13.972789
mAP_valid_abs_values_18 70.9076 15.265083
mAP_valid_abs_values_19 68.7420 15.399282
mAP_valid_abs_values_4 67.5056 12.867583
mAP_valid_abs_values_20 66.6412 15.394766
mAP_valid_abs_values_2 65.4016 9.059835
mAP_valid_abs_values_12 65.3108 13.271108
mAP_valid_abs_values_21 64.0056 9.514047
mAP_valid_abs_values_14 63.0580 9.092967
mAP_valid_abs_values_8 63.0324 7.112824
mAP_valid_abs_values_17 61.0328 6.649189
mAP_valid_abs_values_23 60.5804 6.377480
mAP_valid_abs_values_15 59.9388 3.684010
mAP_valid_abs_values_22 59.7108 1.987400
mAP_valid_abs_values_26 59.1972 2.754980
mAP_valid_abs_values_25 59.0892 2.678659


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_8 62.393600 5.609268
mAP_test_abs_values_23 62.072400 0.855415
mAP_test_abs_values_13 61.808000 9.617606
mAP_test_abs_values_25 61.674400 2.769447
mAP_test_abs_values_22 61.600400 2.616833
mAP_test_abs_values_21 61.485600 0.936612
mAP_test_abs_values_10 61.449200 8.447344
mAP_test_abs_values_14 61.414000 5.849064
mAP_test_abs_values_26 61.213200 3.157670
mAP_test_abs_values_2 61.106400 0.905386
mAP_test_abs_values_19 60.828400 6.366713
mAP_test_abs_values_15 60.603600 2.701689
mAP_test_abs_values_17 60.565200 0.714540
mAP_test_abs_values_12 60.537600 2.164862
average_map 60.503984 0.819719
mAP_test_abs_values_6 60.434800 6.985568
mAP_test_abs_values_5 60.289600 1.145915
mAP_test_abs_values_4 60.224800 2.745266
mAP_test_abs_values_11 60.064000 6.897371
mAP_test_abs_values_7 59.983600 6.193833
mAP_test_abs_values_3 59.931200 1.734655
mAP_test_abs_values_18 59.284400 3.048217
mAP_test_abs_values_20 59.134000 3.058660
mAP_test_abs_values 58.910000 1.429146
mAP_test_abs_values_9 58.279600 3.964504
mAP_test_abs_values_16 57.311600 4.299832
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_abs_values mAP_valid_abs_values_2 mAP_valid_abs_values_3 mAP_valid_abs_values_4 mAP_valid_abs_values_5 mAP_valid_abs_values_6 mAP_valid_abs_values_7 mAP_valid_abs_values_8 mAP_valid_abs_values_9 mAP_valid_abs_values_10 mAP_valid_abs_values_11 mAP_valid_abs_values_12 mAP_valid_abs_values_13 mAP_valid_abs_values_14 mAP_valid_abs_values_15 mAP_valid_abs_values_16 mAP_valid_abs_values_17 mAP_valid_abs_values_18 mAP_valid_abs_values_19 mAP_valid_abs_values_20 mAP_valid_abs_values_21 mAP_valid_abs_values_22 mAP_valid_abs_values_23 mAP_valid_abs_values_25 mAP_valid_abs_values_26
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 68.37 65.62 62.78 62.22 66.23 59.08 55.79 65.66 67.73 66.64 61.94 59.19 65.92 69.33 63.05 58.05 64.53 65.59 48.51 61.12 65.82 66.16 67.21 65.33 65.58
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 68.20 62.28 67.24 63.71 64.84 62.34 57.31 65.37 66.57 65.00 61.40 60.71 65.61 62.86 65.27 64.89 65.44 80.75 61.27 58.40 62.14 64.95 66.70 68.03 68.45
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 64.74 63.62 56.51 62.24 61.92 62.08 65.69 61.39 63.12 64.24 60.56 61.79 87.10 60.02 65.89 63.95 61.63 62.28 59.09 59.26 64.43 62.57 64.12 63.12 62.98
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 71.63 71.01 68.87 72.86 65.75 66.28 52.33 70.72 69.71 69.62 63.73 62.72 67.67 66.51 66.65 75.97 69.87 67.94 43.72 65.17 70.15 69.81 66.60 66.17 70.97
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 66.02 67.08 63.26 64.44 63.59 62.18 86.68 61.56 66.04 64.95 61.64 60.61 64.28 63.33 65.01 63.63 64.21 64.56 61.17 60.41 69.03 67.75 63.79 66.70 63.47
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 65.93 63.97 62.87 65.07 66.21 56.35 55.68 65.35 87.18 64.97 60.30 60.50 56.87 64.98 63.06 63.72 63.21 64.10 61.93 59.75 66.79 68.89 62.23 64.56 65.07
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 67.58 66.82 66.14 66.51 74.73 61.83 57.37 67.78 69.95 68.43 62.89 66.38 70.33 65.18 65.88 63.67 68.64 65.64 61.94 62.41 67.30 66.56 69.13 66.34 68.04
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 58.62 62.09 65.54 66.28 61.68 60.81 65.21 61.38 59.34 64.62 59.60 59.97 62.47 59.40 64.30 64.62 64.82 61.93 60.60 59.91 66.04 64.38 64.45 67.52 63.01
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.53 62.74 64.39 64.03 86.68 60.35 65.91 62.88 63.17 63.80 60.97 61.54 62.83 61.20 65.91 60.72 60.69 63.47 60.69 58.51 63.84 64.44 62.72 64.53 62.64
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 65.44 61.40 61.10 65.25 64.80 59.64 63.15 63.02 64.78 61.44 60.84 59.71 87.78 62.64 62.34 63.80 62.27 61.76 58.18 59.43 64.48 63.84 62.32 66.20 66.27
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 65.55 65.59 64.78 61.61 64.71 59.20 54.62 64.38 64.49 66.82 63.20 58.30 61.61 61.87 61.80 62.71 61.54 63.85 59.75 59.95 62.30 63.18 63.15 62.75 62.69
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 66.47 64.73 63.32 64.49 64.87 62.01 66.87 64.63 64.15 62.51 59.20 59.03 64.50 62.32 63.84 67.19 65.54 63.40 59.49 57.50 67.09 63.80 68.22 65.74 67.35
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 67.03 64.19 56.95 63.81 60.94 64.67 65.05 62.46 63.43 54.37 56.47 63.51 64.68 63.70 61.45 63.25 61.09 64.53 58.98 63.46 67.46 65.03 63.54 67.04 65.84
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 65.10 67.66 68.14 66.10 64.86 62.40 65.70 65.89 65.97 64.24 60.81 60.81 54.60 64.30 65.57 64.52 65.70 67.77 60.74 61.45 64.57 64.24 60.94 64.34 62.28
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 65.64 65.06 64.95 65.96 64.71 62.16 78.06 57.81 63.14 65.11 63.03 62.97 65.27 64.14 64.50 61.53 63.07 69.06 59.89 59.13 64.92 67.46 65.81 66.75 69.14
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 67.68 68.93 68.88 67.94 67.85 66.44 69.21 64.78 66.59 64.92 67.51 63.61 67.26 64.58 66.57 71.89 69.79 66.18 65.79 63.18 65.28 71.54 67.96 68.13 68.20
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 68.45 66.44 57.87 62.97 57.16 43.72 79.22 78.65 63.73 65.90 62.13 60.09 89.08 60.59 63.28 54.04 63.36 64.43 57.30 61.77 63.84 61.54 64.79 67.58 60.06
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 67.38 63.45 66.94 67.16 65.95 59.19 56.12 64.03 66.74 64.89 57.94 65.81 59.34 86.95 61.57 65.74 64.13 66.61 61.11 66.23 65.37 65.37 62.85 67.57 65.24
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 63.27 61.16 63.64 63.89 63.04 59.41 87.96 62.02 60.42 60.50 88.80 57.82 90.78 60.42 61.33 62.40 62.97 62.51 84.02 88.94 65.12 61.35 62.71 66.26 62.31
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.66 88.44 62.31 61.96 60.94 91.28 87.20 63.64 89.36 62.82 86.98 90.70 56.04 60.84 61.22 84.67 59.35 61.39 59.15 59.83 63.82 61.67 61.13 63.62 59.53
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 88.83 62.63 62.88 61.70 61.02 91.52 62.38 60.62 62.78 62.57 91.21 60.65 92.54 83.03 62.55 91.64 60.60 61.60 60.32 57.10 60.35 62.67 62.53 61.87 60.43
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 58.00 63.55 65.35 64.01 63.21 90.13 66.64 65.16 62.63 61.24 59.39 61.20 89.55 90.74 62.02 60.47 62.25 62.40 59.10 59.11 61.70 61.66 61.13 68.24 60.07
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 63.70 62.37 62.03 88.84 60.23 61.44 64.98 60.90 62.50 63.05 89.51 60.58 91.12 61.37 61.74 61.97 61.88 60.87 90.22 58.54 62.27 61.39 63.06 60.80 58.31
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 86.78 62.72 64.46 62.61 88.36 59.86 60.86 60.01 63.54 90.09 91.73 57.20 91.82 60.32 60.06 60.89 60.79 63.65 57.56 59.02 63.41 62.58 59.24 63.81 63.14
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 63.48 65.16 64.33 64.38 64.33 89.10 88.51 61.65 43.72 63.83 58.95 60.21 63.52 62.82 63.10 88.23 60.38 84.69 60.37 59.06 62.90 64.29 60.74 60.24 62.88
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.67 64.49 61.42 62.08 60.72 90.32 86.21 59.43 88.09 61.24 90.18 59.40 90.28 59.57 62.97 60.40 61.65 58.75 59.69 58.14 59.88 62.49 58.55 60.71 62.26
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 63.11 64.46 88.09 62.35 62.15 62.14 82.81 63.12 49.89 63.73 87.53 61.40 63.48 61.57 62.47 63.82 61.98 61.60 60.14 91.03 64.82 61.79 61.32 59.75 61.32
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 88.46 86.61 61.60 60.41 63.10 59.16 85.88 60.31 55.85 62.92 90.63 58.39 90.68 61.86 60.50 62.60 60.27 63.86 91.04 58.40 61.64 59.96 60.87 61.77 60.26
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 64.52 61.93 74.37 61.89 63.27 59.53 88.48 60.54 60.39 62.14 59.26 56.64 78.46 89.22 64.01 85.55 59.32 89.74 60.38 56.91 66.98 64.43 59.66 58.94 61.59
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 64.88 61.51 86.76 60.04 65.18 90.99 87.70 60.12 61.58 43.72 90.08 91.36 61.08 85.45 58.94 56.47 61.12 59.12 90.94 56.10 61.38 60.35 61.98 55.09 61.57
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 64.71 60.70 62.10 87.85 61.14 91.88 88.30 59.57 43.72 87.16 59.27 92.18 84.02 59.93 61.20 88.62 60.33 59.00 90.56 55.89 59.57 60.94 56.45 60.44 61.52
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 88.57 62.53 86.74 61.84 61.35 92.60 88.93 61.47 89.55 62.20 92.17 59.70 84.94 62.20 43.72 60.71 59.85 61.03 59.30 58.30 64.25 62.34 59.50 62.20 58.68
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.22 64.25 87.63 63.04 63.92 60.11 88.64 62.74 64.17 87.34 60.43 57.99 87.00 61.27 64.76 92.24 59.90 56.52 59.80 92.46 59.68 60.61 61.01 57.17 59.93
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 64.49 63.25 61.96 61.22 62.59 89.97 88.17 63.16 89.63 62.17 91.99 58.58 61.24 55.73 62.05 46.94 62.82 59.63 59.87 89.60 63.15 63.13 60.36 51.48 59.83
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 89.13 62.47 61.20 62.12 62.08 58.95 87.86 62.03 89.96 62.83 61.02 55.65 43.72 60.36 61.93 92.22 63.77 60.02 58.25 56.71 61.97 57.70 88.11 61.05 60.48
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 88.72 61.06 86.23 61.50 62.09 60.60 86.75 61.45 90.22 62.58 60.17 56.69 92.51 60.05 59.89 59.00 59.55 91.71 58.66 90.48 64.72 55.75 59.63 61.24 59.41
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 88.03 64.43 89.80 62.32 89.22 59.10 88.69 59.29 90.67 62.82 92.44 60.30 60.73 60.90 60.02 45.81 61.15 90.98 59.98 56.88 89.43 58.24 57.67 58.24 59.04
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 65.25 62.53 62.98 88.91 63.72 59.18 66.74 61.76 63.52 64.78 91.15 60.24 91.00 61.57 61.56 91.71 61.03 90.47 57.54 91.96 65.10 58.98 60.12 58.59 65.50
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.41 89.64 64.51 60.15 88.57 91.93 84.97 59.55 61.58 89.38 87.44 89.31 89.54 58.04 60.00 91.49 57.67 61.25 84.20 55.10 59.92 58.83 59.86 58.21 57.07
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 87.15 61.02 89.21 89.45 89.51 59.47 90.45 61.91 89.72 61.17 91.42 92.42 91.92 91.66 59.65 92.11 61.52 92.24 57.28 59.07 62.80 61.12 58.26 49.09 60.25
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 87.45 64.21 62.42 62.60 63.56 91.34 89.45 62.28 60.89 60.11 59.25 59.21 92.45 60.52 61.51 90.03 60.77 60.42 92.24 86.88 59.79 60.05 57.43 59.66 49.26
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 63.03 89.71 63.81 61.33 62.54 91.95 87.41 60.60 61.73 89.97 55.43 60.38 88.64 60.93 60.68 90.69 59.64 59.23 93.43 58.29 56.40 58.01 58.74 59.47 59.36
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 89.47 61.30 61.12 62.20 87.85 90.42 89.08 61.95 60.60 82.15 89.54 57.66 91.40 60.55 61.03 88.85 92.48 60.05 58.38 58.68 57.06 62.07 90.09 59.18 57.38
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 88.33 64.65 62.29 61.26 62.48 57.16 86.62 61.54 90.72 61.19 59.23 43.72 91.18 59.52 61.15 90.49 59.75 91.46 60.88 58.32 59.05 63.79 60.61 60.63 57.94
Size of the All data:  (100, 28)
Size of the Sig data:  (44, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_abs_values mAP_test_abs_values_2 mAP_test_abs_values_3 mAP_test_abs_values_4 mAP_test_abs_values_5 mAP_test_abs_values_6 mAP_test_abs_values_7 mAP_test_abs_values_8 mAP_test_abs_values_9 mAP_test_abs_values_10 mAP_test_abs_values_11 mAP_test_abs_values_12 mAP_test_abs_values_13 mAP_test_abs_values_14 mAP_test_abs_values_15 mAP_test_abs_values_16 mAP_test_abs_values_17 mAP_test_abs_values_18 mAP_test_abs_values_19 mAP_test_abs_values_20 mAP_test_abs_values_21 mAP_test_abs_values_22 mAP_test_abs_values_23 mAP_test_abs_values_25 mAP_test_abs_values_26
39 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 60.37 59.61 62.79 61.30 60.04 58.65 48.61 60.23 60.99 61.33 59.69 59.64 61.55 58.70 61.14 64.98 60.01 59.73 45.95 58.82 61.66 60.99 61.35 61.42 61.67
31 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 60.29 59.06 60.26 59.11 58.96 59.30 49.40 59.95 57.95 58.74 60.44 59.07 61.23 61.30 59.04 59.70 60.46 59.21 60.62 57.95 62.32 59.21 62.06 60.46 61.03
40 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 59.77 60.61 50.31 61.56 60.59 59.52 61.64 59.37 61.15 60.78 60.79 59.54 58.83 59.18 61.36 59.91 60.02 59.35 59.66 59.65 60.04 61.29 61.47 61.44 61.43
20 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 58.91 58.94 61.11 58.72 61.35 56.96 50.01 59.52 59.68 60.07 58.32 57.76 60.52 60.60 61.13 61.70 59.03 61.34 48.12 57.87 59.88 60.80 61.63 61.83 62.05
29 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 59.76 60.13 60.05 60.35 60.05 59.96 57.98 59.20 60.40 60.34 62.12 59.63 59.23 59.66 60.04 60.79 59.02 58.91 60.55 59.14 60.72 60.68 61.87 60.69 61.55
34 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 59.03 61.01 60.33 60.32 61.74 49.79 49.14 59.19 56.83 59.25 62.16 60.12 49.87 59.80 59.64 60.08 59.62 59.50 59.18 59.86 59.54 59.35 61.98 61.48 61.16
22 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 60.45 61.30 59.49 60.16 61.74 60.65 47.99 59.83 59.84 59.66 58.99 59.42 59.25 65.80 60.63 57.96 59.14 58.87 59.85 59.29 61.48 60.29 60.60 61.10 60.83
42 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 48.54 60.64 59.58 61.28 59.33 60.09 59.38 60.90 49.46 61.36 60.48 59.51 61.29 59.35 59.93 58.57 60.40 59.43 60.17 59.24 60.95 61.78 60.88 60.48 61.94
33 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 56.41 61.73 59.97 59.28 58.14 59.05 60.52 59.74 58.57 59.96 59.29 61.46 59.41 59.37 60.99 60.52 59.27 59.80 60.03 58.47 60.92 62.67 62.42 62.53 62.51
38 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 60.37 60.53 59.30 59.82 59.35 59.11 58.86 59.02 59.90 58.47 60.42 58.41 57.62 59.61 60.41 59.59 59.15 58.18 58.40 58.78 61.00 62.25 62.75 61.69 61.80
43 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 60.00 61.22 59.12 59.67 58.37 58.81 50.37 61.32 59.24 60.53 60.17 59.41 60.04 59.35 60.91 59.38 59.46 59.86 59.17 59.99 62.31 60.74 61.62 61.28 62.22
36 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 60.56 59.71 59.33 60.97 60.61 59.52 60.07 60.49 58.70 60.13 59.75 59.84 59.18 60.14 59.75 60.20 58.81 59.11 58.85 58.62 60.71 61.40 60.08 61.70 60.09
41 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 60.48 58.84 49.00 61.14 60.04 60.17 61.04 58.86 60.07 50.20 50.66 60.31 58.74 60.01 59.48 59.73 62.43 58.82 59.54 59.23 61.64 62.09 62.32 67.02 61.17
35 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 59.24 59.36 60.97 61.00 60.42 59.84 61.00 64.43 60.39 59.34 59.26 59.12 52.63 59.28 61.40 58.31 59.07 58.26 60.52 60.05 61.14 61.89 62.95 60.19 61.50
32 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 60.25 58.63 60.50 60.99 59.26 60.35 49.61 48.88 60.44 60.66 60.22 58.65 61.05 58.78 59.94 59.15 60.67 59.97 59.96 59.63 61.82 61.43 61.69 61.15 60.55
17 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 60.28 60.82 59.19 60.77 60.90 60.16 59.94 61.04 60.33 60.56 60.48 60.03 60.91 61.07 60.33 57.46 58.94 60.43 60.18 59.77 61.13 59.88 60.71 61.06 60.09
37 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 60.28 60.99 49.50 59.37 50.77 48.12 49.53 34.94 60.22 60.52 59.73 59.64 57.88 59.10 60.57 62.90 59.64 59.94 58.51 59.68 61.56 60.80 60.91 60.38 62.57
30 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 59.09 60.24 61.49 60.70 59.90 48.56 50.43 59.64 58.99 59.19 58.53 59.02 46.16 59.23 59.32 58.50 60.31 60.21 58.66 58.28 61.41 62.22 61.58 60.97 61.89
16 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 60.29 58.88 58.27 59.47 60.96 58.90 58.23 59.86 58.78 60.37 51.23 59.47 58.42 58.87 59.18 61.58 60.81 62.28 87.45 56.55 61.40 61.39 61.63 61.38 61.64
3 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 58.28 59.36 61.75 60.33 60.39 59.30 58.88 61.50 58.12 61.65 50.92 59.48 50.25 60.22 61.29 52.21 60.78 59.76 59.47 61.65 61.61 62.72 61.79 61.42 61.71
11 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 58.67 60.27 60.46 61.03 59.32 60.02 61.50 61.64 59.92 61.77 59.33 61.59 59.18 86.26 59.51 59.70 60.43 61.45 61.53 59.63 63.13 61.59 62.18 61.63 62.10
28 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 50.11 61.27 58.98 61.63 60.02 58.25 59.78 61.15 60.09 59.62 62.13 61.93 58.32 59.24 60.30 59.93 60.67 60.68 61.03 60.19 61.77 62.31 62.36 60.26 62.08
23 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 61.92 61.03 61.37 57.93 60.93 61.45 60.20 60.77 61.42 61.28 55.55 61.59 58.63 61.33 60.50 60.24 60.29 60.38 57.35 61.53 60.75 62.25 62.11 61.45 61.00
18 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 57.99 60.21 59.58 61.00 57.73 60.33 58.21 59.95 61.74 58.42 59.64 58.78 58.51 60.82 60.46 59.90 60.54 60.27 59.71 60.40 61.68 62.03 62.78 61.74 61.32
27 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 61.36 60.61 61.13 61.09 61.63 59.73 58.49 61.39 48.12 61.11 60.42 60.58 60.42 60.41 59.95 57.77 60.18 82.74 60.06 60.70 60.98 61.74 61.66 62.07 60.83
15 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 56.37 61.66 60.05 61.79 59.96 57.62 56.24 61.40 58.62 61.16 59.15 61.47 58.97 60.51 61.25 60.77 60.48 60.63 61.58 59.21 62.44 61.45 61.79 61.67 61.68
25 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 60.48 61.67 58.67 59.36 61.23 60.98 58.96 60.32 53.08 61.16 47.75 61.53 60.64 60.57 60.71 59.77 60.35 60.99 62.28 58.05 61.06 62.44 62.17 61.79 62.48
14 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 58.93 57.38 60.72 58.88 60.38 60.76 56.88 61.05 48.85 61.35 59.16 60.53 58.76 60.47 60.43 59.71 59.80 61.07 58.03 60.54 62.28 60.86 60.80 61.32 60.97
21 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 61.27 61.25 52.36 59.48 61.44 62.71 57.80 59.08 60.15 60.77 60.37 50.57 47.44 58.54 57.87 50.54 58.64 56.67 60.82 58.25 61.46 60.99 62.49 62.74 61.97
13 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 60.53 59.99 58.64 60.24 60.74 59.67 58.80 59.26 58.73 48.12 50.01 59.15 59.59 47.94 60.59 49.59 60.45 60.70 58.70 59.60 60.63 62.15 60.19 62.50 61.08
7 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 60.95 59.58 61.08 57.94 60.60 59.52 57.26 59.78 48.12 56.81 62.29 58.54 85.89 60.97 60.67 57.43 60.06 59.56 49.26 59.33 61.27 62.52 63.39 61.86 61.22
12 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 59.05 61.76 55.83 60.60 60.28 58.98 59.89 60.55 57.15 60.13 59.88 62.70 87.16 60.16 48.12 60.31 59.74 60.08 60.77 61.29 60.92 62.25 62.69 62.20 61.64
6 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 57.17 61.06 58.92 61.99 60.47 60.84 58.17 62.50 60.99 58.02 62.78 59.25 57.89 60.58 60.95 59.02 60.57 50.47 60.48 59.35 61.95 62.78 62.90 63.48 62.10
24 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 61.16 60.37 61.35 60.33 61.22 58.91 57.47 61.67 57.69 59.51 57.43 61.43 61.07 49.19 61.04 75.37 59.66 61.18 60.09 59.57 61.78 62.14 61.94 45.10 61.96
26 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 57.99 60.64 60.62 62.36 60.89 58.77 57.33 60.08 58.88 60.71 61.62 58.59 48.12 59.63 60.71 59.56 61.02 60.08 61.37 59.38 62.26 62.76 60.03 62.20 61.50
10 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 58.88 62.32 56.32 60.97 61.41 60.92 88.18 61.11 57.61 60.48 62.32 59.93 58.31 62.18 61.58 60.71 60.72 58.94 60.46 50.61 60.25 49.51 62.36 62.52 61.00
4 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.74 61.52 59.26 62.32 59.41 62.08 58.77 61.93 59.10 61.42 59.79 62.15 62.16 61.21 61.42 65.45 60.75 59.48 61.53 59.45 60.03 60.47 61.95 61.82 62.28
5 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 61.16 61.87 61.27 59.81 61.81 60.11 59.64 61.76 60.67 61.39 60.33 62.39 59.28 60.90 61.75 59.43 61.49 59.45 62.97 59.04 60.33 62.55 62.20 62.42 61.84
1 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 57.80 59.56 61.33 60.44 58.48 59.95 51.41 62.00 61.36 59.18 51.55 51.81 60.01 61.70 62.25 59.72 61.00 61.46 87.31 59.06 61.43 61.60 61.15 62.61 62.49
0 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.59 62.00 59.07 59.52 59.22 61.90 59.49 60.91 59.71 62.32 60.22 59.95 59.59 58.21 62.28 59.05 60.03 59.22 62.90 60.65 61.57 62.42 62.09 48.62 62.01
8 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.69 61.55 61.21 61.31 60.72 59.48 59.22 61.70 61.51 61.44 61.87 61.58 59.52 61.48 61.70 57.64 60.82 62.09 59.37 52.38 62.90 62.33 62.28 62.56 46.25
9 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 61.88 59.48 61.29 60.75 61.99 58.62 59.27 61.15 61.02 59.12 59.17 61.99 60.19 60.59 60.40 59.37 61.36 60.98 59.95 61.87 62.48 62.69 62.56 62.08 62.25
2 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 59.00 61.40 61.28 60.90 59.80 59.80 59.23 60.69 60.77 82.94 49.59 60.17 59.73 61.43 61.99 48.48 58.81 61.99 61.25 61.42 61.60 61.82 59.47 61.39 62.45
19 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 58.01 61.29 61.62 61.59 60.77 60.06 56.64 61.70 58.40 61.11 61.19 48.12 58.59 60.72 60.79 58.74 60.57 58.51 61.65 61.36 61.92 61.68 62.40 62.50 62.12
Size of the test data:  (44, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

key_values = ['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']
print('Are the keys of the valid and test dfs same?: ',dt_mw[key_values].equals(test_data_mw1[key_values]))
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.12 -1.01 -4.42 -4.75 -28.54 -1.30 -5.39 -3.14 -4.60 -3.84 -1.68 -0.08 -3.42 -1.83 -4.92 -0.20 -1.42 -3.67 -0.66 -0.04 -2.92 -1.77 -0.30 -2.00 -0.13 25
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.40 -8.11 -9.69 -7.17 -6.95 -6.28 -9.27 -3.74 -6.26 -4.36 -7.03 -3.58 -6.35 -3.51 -6.24 -14.43 -10.85 -5.75 -5.61 -3.41 -4.15 -11.66 -7.25 -7.07 -8.11 25
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.91 -3.22 -6.98 -4.60 -5.88 -3.04 -7.91 -5.42 -8.62 -6.26 -0.96 -1.64 -4.38 -1.56 -6.23 -5.19 -4.98 -21.54 -0.65 -0.45 0.18 -5.74 -4.64 -7.57 -7.42 24
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -12.72 -12.07 -7.76 -14.14 -4.40 -9.32 -2.32 -11.20 -10.03 -9.55 -5.41 -4.96 -7.15 -5.91 -5.52 -14.27 -10.84 -6.60 4.40 -7.30 -10.27 -9.01 -4.97 -4.34 -8.92 24
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -6.26 -6.95 -3.21 -4.09 -3.54 -2.22 -28.70 -2.36 -5.64 -4.61 0.48 -0.98 -5.05 -3.67 -4.97 -2.84 -5.19 -5.65 -0.62 -1.27 -8.31 -7.07 -1.92 -6.01 -1.92 24
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.13 -5.52 -6.65 -6.35 -12.99 -1.18 -9.38 -7.95 -10.11 -8.77 -3.90 -6.96 -11.08 0.62 -5.25 -5.71 -9.50 -6.77 -2.09 -3.12 -5.82 -6.27 -8.53 -5.24 -7.21 24
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -10.08 -1.45 -5.96 -5.00 -2.35 -0.72 -5.83 -0.48 -9.88 -3.26 0.88 -0.46 -1.18 -0.05 -4.37 -6.05 -4.42 -2.50 -0.43 -0.67 -5.09 -2.60 -3.57 -7.04 -1.07 24
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.29 -3.21 -5.45 -6.46 -6.05 -10.63 -5.69 -4.39 -7.75 -5.70 0.59 -6.79 -13.18 -27.72 -2.25 -7.24 -3.82 -6.40 -2.45 -7.95 -3.96 -3.15 -1.27 -6.60 -3.35 24
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.86 -8.30 -7.17 -5.10 -4.44 -2.56 -4.70 -1.46 -5.58 -4.90 -1.55 -1.69 -1.97 -5.02 -4.17 -6.21 -6.63 -9.51 -0.22 -1.40 -3.43 -2.35 2.01 -4.15 -0.78 24
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -6.55 -5.35 -7.95 -2.67 -0.90 -4.50 -4.01 -3.60 -3.36 -4.17 -5.81 -3.20 -5.94 -3.69 -1.97 -3.52 1.34 -5.71 0.56 -4.23 -5.82 -2.94 -1.22 -0.02 -4.67 23
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.39 -6.43 -4.45 -4.97 -5.45 -1.81 -28.45 -8.93 -2.70 -4.45 -2.81 -4.32 -4.22 -5.36 -4.56 -2.38 -2.40 -9.09 0.07 0.50 -3.10 -6.03 -4.12 -5.60 -8.59 23
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -6.90 -2.96 -2.54 -4.75 -4.47 -6.56 -6.54 -6.16 -30.35 -5.72 1.86 -0.38 -7.00 -5.18 -3.42 -3.64 -3.59 -4.60 -2.75 0.11 -7.25 -9.54 -0.25 -3.08 -3.91 23
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.07 -0.87 -1.80 -5.43 -5.45 -0.53 -4.29 -4.00 -4.88 -2.97 -0.42 -1.30 -30.16 -3.03 -1.93 -4.21 -3.12 -3.58 0.22 -0.65 -3.48 -1.59 0.43 -4.51 -4.47 23
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -2.98 -2.28 -5.37 -4.42 -2.08 -0.51 -29.73 -2.16 -1.64 -0.13 -37.57 1.65 -32.36 -1.55 -2.15 -0.82 -2.16 -0.23 3.43 -32.39 -3.72 0.04 -1.08 -4.88 -0.67 22
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.00 -6.01 0.01 -0.92 -6.19 -0.43 -7.18 -5.43 -6.74 -5.31 -2.25 0.45 -4.37 -10.63 -1.91 6.93 -4.52 -5.86 -2.56 -2.30 -4.16 -5.17 -5.86 -3.91 -3.91 22
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.91 -5.02 -3.99 -3.52 -4.26 -2.49 -6.80 -4.14 -5.45 -2.38 0.55 0.81 -5.32 -2.18 -4.09 -6.99 -6.73 -4.29 -0.64 1.12 -6.38 -2.40 -8.14 -4.04 -7.26 22
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.55 -4.37 -5.66 -1.94 -6.34 -0.39 -4.25 -3.06 -5.25 -6.29 -3.03 1.11 -1.57 -2.52 -0.89 -3.33 -2.08 -3.99 -0.58 0.04 0.01 -2.44 -1.53 -1.47 -0.47 22
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.97 -3.01 -6.20 -0.68 -1.33 -2.56 -4.05 -2.02 -1.97 -3.46 0.23 -2.25 -28.27 -0.84 -4.53 -4.04 -1.61 -2.93 0.57 0.39 -4.39 -1.28 -2.65 -1.68 -1.55 22
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.17 -5.45 -8.37 -3.60 -6.39 4.40 -29.69 -43.71 -3.51 -5.38 -2.40 -0.45 -31.20 -1.49 -2.71 8.86 -3.72 -4.49 1.21 -2.09 -2.28 -0.74 -3.88 -7.20 2.51 21
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -3.33 -2.88 -0.61 -0.89 -1.37 -31.06 -30.70 -1.49 -31.94 -2.66 -34.56 2.85 -0.17 -6.54 -1.01 28.43 -3.16 1.55 0.22 -30.03 -1.37 -0.99 1.58 -6.38 2.13 19
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -2.12 -4.55 -3.20 -3.29 -2.70 -29.37 -30.02 -0.26 4.40 -2.72 1.47 0.37 -3.10 -2.41 -3.15 -30.46 -0.20 -1.95 -0.31 1.64 -1.92 -2.55 0.92 1.83 -2.05 19
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -2.63 -2.79 -29.42 -2.99 -0.92 -1.16 -23.85 -2.80 3.19 -2.57 -39.78 0.13 -2.84 -1.00 -1.76 -4.05 -1.63 -0.61 2.14 -32.98 -3.76 0.65 0.85 2.04 1.16 18
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.35 -1.52 -28.12 0.20 -4.44 -31.32 -28.90 -0.86 -2.85 4.40 -40.07 -32.21 -1.49 -37.51 1.65 -6.88 -0.67 1.58 -32.24 3.50 -0.75 1.80 -1.79 7.41 -0.49 18
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -3.25 -0.68 -22.01 -2.41 -1.83 3.18 -30.68 -1.46 -0.24 -1.37 1.11 -6.07 -31.02 -30.68 -6.14 -35.01 -0.68 -33.07 0.44 1.34 -5.52 -3.44 2.83 3.80 0.38 18
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.53 -29.23 -0.88 -1.53 -2.72 1.60 -29.00 0.74 -7.00 -1.57 -31.47 2.14 -31.92 -1.39 -0.07 -2.89 -0.47 -2.79 -33.01 2.14 0.64 0.90 -0.07 -0.45 0.71 18
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.78 -1.34 -0.66 -30.91 0.70 0.01 -4.78 -0.13 -1.08 -1.77 -33.96 1.01 -32.49 -0.04 -1.24 -1.73 -1.59 -0.49 -32.87 2.99 -1.52 0.86 -0.95 0.65 2.69 18
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.16 -2.36 -2.42 -0.67 -1.70 -31.50 -0.88 1.02 -2.86 -0.80 -31.88 0.94 -33.36 3.23 -3.04 -31.94 -0.17 -0.15 1.21 2.53 2.78 -1.08 -0.35 -0.24 1.67 18
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.38 -29.08 -0.56 -1.63 -0.55 -31.98 -28.32 -2.14 -31.24 -1.17 -36.06 -31.22 -5.79 -0.62 0.07 -32.46 1.43 -1.63 0.32 1.82 -2.21 1.05 0.66 -2.20 2.18 18
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.79 -2.51 -4.88 -1.61 -30.63 0.47 -2.65 -0.06 -1.80 -31.67 -32.09 1.58 -33.31 0.50 0.40 -0.99 -0.25 -3.38 2.15 1.38 -1.73 -0.55 3.54 -2.07 -1.82 18
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.89 -2.28 -6.37 -2.38 -3.19 -31.88 -6.86 -4.01 -2.54 -1.62 2.74 0.73 -31.23 -31.50 -1.72 -0.54 -1.58 -1.72 1.93 1.08 0.07 0.65 1.23 -7.98 2.01 17
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.52 -0.77 -30.91 -1.24 -1.07 -33.62 -29.04 -0.92 -32.40 -2.07 -32.29 3.00 2.22 -2.04 4.40 -0.40 -0.11 -0.95 1.47 2.99 -3.33 -0.09 3.19 -0.00 2.96 17
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.09 -0.66 -1.71 -29.10 -1.91 0.93 -7.10 -0.00 -2.85 -3.39 -30.82 2.15 -31.72 -0.67 0.19 -32.28 0.46 -31.02 5.43 -32.92 -4.77 3.57 2.08 3.83 -3.66 16
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.56 0.98 -30.14 -29.93 -30.29 2.43 -30.96 -1.00 -30.01 1.15 -31.20 -32.47 -32.33 -33.45 2.63 -33.06 -1.49 -33.02 5.62 1.58 -1.23 1.30 3.83 -0.47 1.76 16
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.30 -2.83 -1.37 -0.29 -0.76 -32.70 -29.97 1.97 -29.47 -0.08 -31.03 2.07 -31.31 0.94 -1.72 0.37 -1.17 1.88 1.89 1.07 2.56 -1.04 3.24 0.96 -0.58 15
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.05 -3.19 -28.71 -1.05 -3.45 0.73 -30.47 -0.24 -3.18 -29.32 2.35 1.26 -29.11 -0.69 -3.81 -33.22 0.67 -6.05 0.68 -33.11 2.27 2.17 1.89 6.31 2.17 15
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -3.76 -1.12 -1.02 -29.91 -0.54 -32.36 -31.04 0.21 4.40 -30.35 3.02 -33.64 1.87 1.04 -0.53 -31.19 -0.27 0.56 -41.30 3.44 1.70 1.58 6.94 1.42 -0.30 14
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -31.14 -1.83 -0.58 0.24 -1.19 -0.18 -30.53 -1.95 -31.08 -2.12 0.60 2.94 4.40 -0.73 -1.22 -32.66 -2.75 0.06 3.12 2.67 0.29 5.06 -28.08 1.15 1.02 14
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.15 -30.23 -2.52 -0.58 -0.55 -33.33 -28.14 0.55 -0.71 -30.85 3.74 1.61 -28.45 -0.34 -0.28 -31.32 1.72 1.75 -33.48 3.58 6.08 4.68 3.82 2.61 2.89 14
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.76 -2.66 -1.21 -1.29 -2.84 -31.86 -30.23 -0.58 0.62 1.33 2.62 2.37 -32.93 0.96 0.19 -32.39 0.05 1.67 -32.87 -34.50 3.11 2.28 4.85 2.90 -3.01 13
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.47 0.10 0.16 -1.30 -28.05 -30.62 -29.85 -1.26 0.17 0.79 -39.95 2.51 -31.67 0.88 0.96 -40.37 -33.67 1.94 2.87 2.74 4.54 -0.25 -30.62 2.21 5.07 12
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.84 1.26 -29.91 -0.53 -0.68 0.32 1.43 -0.34 -32.61 -2.10 2.15 3.24 -34.20 2.13 1.69 1.71 1.17 -32.77 1.80 -39.87 -4.47 -6.24 2.73 1.28 1.59 12
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -32.61 -30.08 -3.18 0.29 -30.09 -31.98 -33.56 2.45 -0.22 -30.20 -35.89 -37.50 -29.53 3.66 2.25 -31.77 3.33 0.21 3.11 3.96 1.51 2.77 1.29 4.40 5.42 12
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.32 -3.36 -0.67 0.33 -1.71 2.90 -29.98 0.16 -32.32 -0.08 1.96 4.40 -32.59 1.20 -0.36 -31.75 0.82 -32.95 0.77 3.04 2.87 -2.11 1.79 1.87 4.18 12
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.29 -2.91 -30.54 -0.00 -29.81 2.98 -29.92 2.64 -31.57 -1.40 -32.65 1.85 1.43 0.31 1.40 19.64 -0.40 -31.50 1.55 2.57 -29.40 2.23 4.28 3.58 3.24 11
Are the keys of the valid and test dfs same?:  False

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_abs_values_13 75.610000 14.544143
mAP_valid_abs_values_7 75.491818 13.203204
mAP_valid_abs_values 73.560909 11.303586
mAP_valid_abs_values_11 71.349091 14.550901
mAP_valid_abs_values_16 70.770682 14.126503
mAP_valid_abs_values_6 69.324318 14.580743
mAP_valid_abs_values_9 68.255909 12.773298
mAP_valid_abs_values_3 67.494773 9.450812
mAP_valid_abs_values_18 67.455455 10.726516
mAP_valid_abs_values_5 66.901136 9.013690
mAP_valid_abs_values_10 66.276591 9.462459
mAP_valid_abs_values_2 66.124091 7.519382
mAP_valid_abs_values_4 65.740909 7.734426
mAP_valid_abs_values_14 65.325909 9.396410
mAP_valid_abs_values_19 64.623864 12.420444
mAP_valid_abs_values_20 64.269091 11.644751
mAP_valid_abs_values_21 64.045682 4.926097
mAP_valid_abs_values_23 63.347500 6.435589
mAP_valid_abs_values_12 63.337045 10.618225
mAP_valid_abs_values_17 63.007273 5.282553
mAP_valid_abs_values_22 62.902273 3.264319
mAP_valid_abs_values_8 62.830909 3.452881
mAP_valid_abs_values_25 62.412500 4.383406
mAP_valid_abs_values_26 62.195455 3.936205
mAP_valid_abs_values_15 62.181818 3.496953


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_abs_values_21 61.729432 2.681800
mAP_test_abs_values_26 61.439943 1.789790
mAP_test_abs_values_25 61.346591 2.705651
mAP_test_abs_values_23 61.335909 3.009567
mAP_test_abs_values_22 61.173864 2.546678
mAP_test_abs_values_18 60.340170 4.630166
mAP_test_abs_values_4 60.209659 1.771109
mAP_test_abs_values_15 60.174943 2.057500
mAP_test_abs_values_14 60.164091 4.441917
mAP_test_abs_values_8 60.134943 4.750951
mAP_test_abs_values_2 60.115057 2.394050
mAP_test_abs_values_10 59.947045 3.897951
mAP_test_abs_values_12 59.803977 2.197745
average_map 59.742191 0.969075
mAP_test_abs_values_5 59.733693 2.197233
mAP_test_abs_values_17 59.720000 2.608334
mAP_test_abs_values_19 59.700170 5.950423
mAP_test_abs_values_20 59.626648 4.476815
mAP_test_abs_values_3 58.929205 3.265148
mAP_test_abs_values_11 58.850341 3.367100
mAP_test_abs_values_16 58.743125 4.123951
mAP_test_abs_values_6 58.700795 5.090062
mAP_test_abs_values_13 58.582898 6.210478
mAP_test_abs_values_9 58.525511 4.544155
mAP_test_abs_values 58.212216 4.892959
mAP_test_abs_values_7 56.314545 5.880173


Summary using radar plot

Code
def extract_number(text):
    if isinstance(text, str):
        matches = re.findall(r'\d+', text)
        return int(matches[0]) if matches else 1
    return 1

res_valid1['id'] = res_valid1.index.to_series().apply(extract_number)
res_test1['id'] = res_test1.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid1,res_test1])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test1 = res_test1.sort_values(by=['id']).reset_index().query("index !='average_map'")
data_range1 = np.array(list(res_test1['mean']) + list(res_valid1['mean']))
categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test1['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid1['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1 + 1]
    )),
  showlegend=True
)

fig.show()

##############


res_valid2['id'] = res_valid2.index.to_series().apply(extract_number)
res_test2['id'] = res_test2.index.to_series().apply(extract_number)



res_comb = pd.concat([res_valid2,res_test2])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res_test2 = res_test2.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res_test2['mean']) + list(res_valid2['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res_test2['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res_valid2['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()




  • In these experimental results, the thresholding is based on a fixed value of 0. This decision is informed by the fact that the binary-like hash values are symmetrically distributed between -1 and 1.
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
0 372 8 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 64.86 63.05 63.35 63.00 52.78 59.21 63.32 60.91 60.60 61.69 60.76 64.31 58.08 58.70 62.38 58.70 61.58 63.72 60.14 63.00 67.91 60.75 60.67 62.61 65.72
3 372 8 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 54.76 57.69 62.24 62.66 61.73 57.74 63.58 60.10 64.86 60.03 57.59 56.79 60.53 56.26 60.94 43.72 63.32 60.17 57.83 56.33 64.19 64.86 60.32 57.79 58.81
12 372 8 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 56.32 43.72 69.38 64.57 62.54 62.11 57.69 62.84 66.21 58.12 43.72 61.99 61.92 64.66 63.93 61.36 63.93 60.34 62.02 57.77 60.34 43.72 65.40 63.95 63.25
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 65.42 65.02 64.94 65.93 64.71 61.95 78.06 57.81 63.08 65.07 62.43 62.91 65.24 64.06 64.44 61.44 62.85 68.90 59.89 59.04 64.92 67.46 65.79 66.72 68.90
64 372 8 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 54.06 43.72 87.33 63.25 62.86 55.95 88.30 58.64 63.64 65.12 58.69 59.83 89.95 55.99 60.41 60.30 60.33 59.94 56.73 59.15 66.14 68.13 61.54 61.95 57.87
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 85.92 62.52 86.84 61.52 60.48 43.72 56.28 61.21 87.16 64.16 88.25 58.68 61.32 58.74 59.05 89.89 61.15 87.99 92.21 56.04 60.29 60.23 59.11 59.73 59.51
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 64.68 60.43 62.10 87.54 61.14 91.50 87.96 59.34 43.72 87.16 59.27 55.86 83.03 59.93 61.03 88.58 60.33 59.00 90.56 55.85 59.44 60.29 56.27 60.43 61.35
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 88.42 62.49 86.25 61.84 61.35 92.42 88.26 61.40 89.55 62.08 92.09 59.67 84.68 61.43 43.72 60.59 59.85 61.00 59.26 58.30 63.92 62.27 59.44 62.05 58.68
128 372 8 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 62.01 61.34 60.30 61.36 63.42 56.15 60.31 60.65 87.72 60.90 59.58 57.69 88.98 59.80 59.75 91.95 59.32 60.54 56.38 57.89 58.39 58.41 57.29 59.23 57.44
131 372 8 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 88.80 61.63 86.18 61.20 62.11 59.05 88.19 51.46 56.17 55.28 58.69 57.99 90.41 60.19 58.68 60.03 59.19 88.77 59.30 88.92 57.61 59.94 57.11 58.98 58.37
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 89.47 61.30 61.12 61.95 87.38 90.42 88.83 61.92 60.35 81.76 88.96 57.45 91.40 60.55 60.78 88.80 92.48 60.05 58.25 58.30 56.84 62.01 89.98 59.06 57.26
143 372 8 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 60.64 64.23 61.81 88.72 59.45 59.28 88.60 59.60 60.91 62.62 91.43 59.09 90.84 60.33 60.39 84.68 57.49 89.93 43.72 58.65 56.48 59.38 58.97 58.05 59.57
192 372 8 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 56.46 60.72 56.22 64.08 64.95 58.67 52.60 58.12 56.16 58.84 63.71 63.64 71.15 61.48 60.76 62.32 62.83 59.74 59.00 59.25 64.38 60.63 61.50 60.78 60.09
195 372 8 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 86.10 56.16 58.91 60.65 56.99 54.28 87.14 57.53 58.88 58.31 55.89 54.51 87.94 57.90 57.58 90.10 50.19 59.03 57.39 55.41 62.10 61.45 58.31 58.28 56.47
204 372 8 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 67.38 56.58 66.44 64.31 63.48 66.39 43.72 62.81 64.61 65.92 56.96 43.72 56.96 63.78 60.90 43.72 64.55 65.03 59.62 58.64 67.02 62.37 60.67 65.48 56.75
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 67.68 68.79 68.78 67.94 67.85 66.43 69.18 64.75 66.58 64.38 67.38 63.50 67.26 64.36 66.40 71.82 69.49 66.18 65.72 63.18 64.90 71.23 67.92 68.07 68.20
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.20 64.05 87.63 62.79 63.92 60.11 88.10 62.45 64.07 87.34 60.39 57.83 86.95 61.27 64.63 92.24 59.32 56.39 59.77 92.46 59.18 60.61 60.90 57.16 59.91
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 64.49 63.22 61.79 61.09 62.59 89.97 87.92 63.02 89.38 62.12 91.86 58.58 61.06 55.48 62.05 46.71 62.76 59.58 59.86 89.58 63.15 62.28 60.32 50.80 59.49
268 372 8 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 56.95 59.12 55.68 60.01 87.42 59.49 43.72 60.77 60.78 62.80 91.23 56.31 90.20 60.30 59.52 61.62 60.90 61.31 58.27 56.09 62.42 61.54 58.42 59.90 58.64
271 372 8 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 84.02 60.94 62.61 87.00 61.58 90.58 43.72 58.39 62.26 89.60 57.26 58.79 90.10 58.56 57.35 90.17 61.33 59.33 57.43 57.88 60.94 60.34 60.88 60.26 58.89
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 87.94 64.65 62.17 61.04 62.46 57.04 86.61 61.29 90.47 61.19 59.23 43.72 91.18 59.52 61.15 90.43 59.74 91.46 60.84 58.32 59.05 63.77 60.16 60.63 57.86
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 88.35 61.23 86.23 60.61 59.33 89.55 90.24 59.74 60.41 60.76 59.04 56.87 88.98 58.23 58.85 59.00 59.01 90.92 93.15 56.00 58.99 57.60 59.09 60.54 60.10
332 372 8 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 63.57 62.59 62.52 62.35 54.84 59.18 89.30 87.38 81.80 59.19 59.46 56.16 87.11 59.22 60.06 61.12 59.85 92.87 56.58 58.80 57.34 60.97 59.20 57.73 59.34
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 88.53 59.96 60.22 61.27 89.95 58.07 90.72 60.70 90.41 90.37 58.59 60.34 82.30 57.75 59.59 91.46 60.03 55.97 57.65 55.78 59.52 61.48 55.21 58.71 59.36
384 372 8 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 43.72 63.22 59.14 60.60 61.19 59.62 86.75 60.39 61.71 58.56 59.09 60.05 61.16 51.61 58.25 61.14 63.22 57.58 49.78 58.72 59.41 61.13 62.95 58.46 62.86
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 68.43 66.34 57.79 62.97 56.31 43.72 79.09 78.38 63.47 65.84 61.40 59.78 89.08 60.16 63.19 53.95 63.36 64.43 57.12 61.72 63.84 61.40 64.75 67.49 60.03
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 67.38 63.05 66.69 66.94 65.87 59.19 56.12 63.72 66.38 64.80 57.94 65.64 59.34 86.56 61.13 65.46 64.13 66.36 60.93 66.19 65.04 64.76 62.84 67.44 64.85
399 372 8 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 82.80 62.61 60.46 53.56 60.69 82.65 54.53 53.15 58.46 58.23 56.55 55.38 87.31 59.93 60.56 59.94 58.80 89.28 56.05 55.28 59.79 59.24 59.36 60.37 60.86
448 372 8 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 55.57 61.82 62.30 59.31 61.50 58.01 85.25 60.41 61.05 89.74 90.62 58.29 89.17 62.83 61.85 89.23 61.40 61.19 58.62 58.62 57.31 61.72 61.60 62.20 57.41
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 88.14 62.84 61.56 60.21 88.38 58.81 89.35 88.82 61.80 61.23 59.60 58.25 89.41 59.19 60.99 55.61 59.68 89.98 58.51 87.52 63.16 61.19 60.15 58.90 60.15
460 372 8 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 62.67 62.13 58.49 63.52 60.76 58.72 87.94 61.25 60.83 61.78 56.54 88.06 88.60 60.72 60.79 55.88 61.57 59.62 60.02 58.71 62.10 58.56 62.14 58.83 59.03
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 89.13 62.47 61.20 62.03 62.08 58.88 87.86 61.97 89.74 62.83 60.90 55.49 43.72 59.43 61.91 91.94 63.77 60.01 57.97 56.71 61.91 57.70 88.09 61.04 60.43
512 372 8 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 88.05 60.61 62.77 61.26 62.76 90.72 62.77 59.57 62.33 61.92 58.92 57.92 43.72 59.72 60.89 81.65 60.93 59.81 59.16 60.36 59.04 60.92 61.19 58.63 58.74
515 372 8 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 64.15 62.50 56.39 61.62 61.73 91.16 89.60 61.43 91.12 60.66 58.01 55.53 86.05 59.33 61.17 84.83 63.09 60.52 59.68 59.13 59.96 60.53 57.69 57.72 59.07
524 372 8 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 85.94 62.43 61.67 61.85 61.53 88.70 88.42 60.99 90.72 61.07 91.47 56.56 61.30 57.87 60.54 54.93 61.29 91.22 56.56 55.39 57.49 59.57 59.60 58.26 59.35
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 87.89 62.31 62.06 62.19 62.80 59.24 88.41 61.47 91.55 85.14 60.77 59.33 90.96 60.50 60.55 88.10 58.87 60.20 58.57 58.00 88.60 58.49 59.77 59.62 56.70
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 67.51 66.81 66.12 66.51 74.73 61.66 57.16 67.62 69.41 68.02 62.68 66.25 70.24 65.14 65.76 63.59 68.62 65.56 61.68 62.39 67.30 66.41 69.03 66.25 67.93
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 58.28 62.01 65.54 65.76 61.46 60.81 64.73 61.38 59.04 64.41 59.11 59.78 62.34 59.18 64.06 64.62 64.73 61.73 60.59 59.86 66.04 64.22 64.29 67.28 62.98
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.53 62.01 64.33 63.83 85.90 60.27 65.88 62.63 63.15 63.80 60.50 61.18 62.77 61.20 65.79 60.62 60.07 63.47 60.67 58.51 63.57 64.35 61.92 64.46 62.49
591 372 8 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 87.51 61.13 63.74 65.85 66.13 43.72 57.99 62.94 65.40 65.93 63.28 59.34 63.15 59.53 61.07 63.72 56.07 65.10 61.87 59.96 64.96 43.72 43.72 61.59 61.56
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 86.78 62.69 64.46 62.29 88.23 59.84 60.84 59.91 63.52 90.09 91.73 57.12 91.82 60.06 59.48 60.73 60.73 63.46 57.44 58.95 63.10 62.49 59.24 63.68 62.98
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 63.25 64.65 64.14 64.25 64.17 89.06 88.04 61.65 43.72 63.50 58.71 60.17 63.52 62.82 62.86 88.07 60.38 84.08 60.33 58.54 62.77 64.09 60.70 59.95 62.66
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.60 64.23 61.25 61.42 60.72 90.32 86.21 59.42 88.00 61.24 90.18 59.28 90.28 59.43 62.93 60.08 61.45 58.34 59.40 57.95 59.84 62.49 58.55 60.35 61.88
655 372 8 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 60.87 61.66 63.98 60.98 63.00 43.72 63.59 58.88 61.96 62.80 59.34 59.57 87.64 60.83 61.28 60.33 62.91 64.17 56.40 58.96 62.21 62.26 62.14 60.77 60.87
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 65.16 62.53 62.79 88.89 63.26 59.18 66.61 61.00 63.52 64.26 90.78 60.05 88.79 61.57 61.30 91.71 60.66 90.47 57.54 91.96 65.10 58.98 59.80 58.59 65.50
707 372 8 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 86.31 62.85 61.44 61.59 86.99 59.39 87.94 60.53 56.35 61.07 59.00 60.06 90.95 59.56 60.84 91.88 60.70 60.23 58.62 58.07 60.33 58.11 59.19 57.84 59.97
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 88.46 62.56 63.61 43.72 88.97 90.42 87.78 60.78 84.99 89.48 60.39 57.76 89.44 57.22 59.08 85.94 59.34 60.60 57.05 92.21 87.43 58.21 58.15 60.01 59.02
719 372 8 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 63.03 87.05 56.19 62.66 88.12 58.30 90.22 59.83 61.53 60.41 55.15 59.01 90.45 58.68 63.08 60.81 59.99 91.11 60.77 89.10 58.98 58.44 61.12 60.42 62.49
768 372 8 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 60.16 61.77 62.59 61.36 54.63 58.52 53.54 43.72 63.77 58.51 57.27 58.21 43.72 60.19 58.07 84.57 59.82 58.65 59.72 56.34 63.00 61.61 62.77 57.33 58.19
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 64.96 61.40 61.01 64.98 64.66 59.58 63.07 62.66 64.15 61.40 60.84 59.65 87.68 62.64 62.34 63.41 62.27 61.58 57.99 59.19 64.23 63.72 62.18 66.20 66.17
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 65.52 65.53 64.55 61.45 64.51 59.20 54.21 64.36 64.08 66.78 62.93 58.25 61.61 61.76 61.80 62.59 61.05 63.72 59.31 59.69 62.18 63.18 63.13 62.75 62.09
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 66.41 64.26 63.32 64.49 64.73 61.80 66.34 64.61 64.06 62.51 59.15 59.03 64.50 62.32 63.75 67.05 65.42 63.31 59.42 57.43 67.05 63.80 67.74 65.61 67.35
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 63.11 64.16 88.09 62.34 61.70 62.14 82.78 62.95 49.83 63.49 87.38 61.40 63.37 61.57 62.46 63.79 61.97 61.47 60.05 90.75 64.82 61.42 61.32 59.75 61.13
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 87.47 62.41 89.51 89.18 63.39 61.01 89.56 83.26 86.89 61.55 91.82 56.69 90.18 60.20 58.71 61.22 59.00 58.02 56.86 58.98 60.75 58.11 60.39 59.49 57.66
844 372 8 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 55.50 60.34 55.93 87.84 60.00 58.14 87.07 59.65 62.18 60.22 57.67 58.22 89.47 59.74 60.94 88.30 50.41 60.28 58.39 57.82 62.07 59.86 60.17 60.76 62.66
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 88.46 86.61 61.60 60.40 63.10 59.16 85.88 60.11 55.63 62.34 90.63 58.39 90.63 61.86 60.48 62.45 60.25 63.86 91.04 58.40 61.51 59.93 60.77 61.60 59.38
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.57 61.95 61.41 63.75 86.41 85.71 89.53 60.79 43.72 83.37 59.06 59.69 88.95 58.75 62.96 90.56 59.49 61.76 57.81 56.14 59.05 62.53 58.91 59.20 61.40
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 85.92 61.84 89.24 88.21 61.23 57.30 88.03 61.34 60.66 60.41 56.87 57.80 91.44 59.93 61.84 89.73 57.28 91.76 58.30 93.22 58.34 57.87 60.68 59.20 58.16
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.32 89.64 64.51 60.15 88.21 91.68 84.95 59.55 61.58 89.38 87.44 88.52 89.54 57.91 60.00 91.01 57.56 61.01 83.96 54.85 59.92 58.83 59.53 58.03 56.89
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 87.15 61.02 89.21 89.40 89.51 59.47 90.29 61.72 89.72 61.05 91.42 92.42 90.91 91.60 59.14 92.11 61.52 92.24 57.28 59.07 62.80 60.77 58.26 49.09 59.96
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 65.91 64.19 56.86 63.70 60.83 64.22 64.98 62.42 63.36 54.32 55.39 63.42 64.12 63.08 60.96 63.25 60.98 64.39 58.98 63.46 67.42 64.95 63.46 66.85 65.81
963 372 8 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 60.69 63.38 63.31 60.97 62.14 58.30 65.03 60.89 62.25 61.48 59.71 56.45 62.62 60.54 62.69 62.77 61.05 64.40 56.54 55.20 63.71 61.08 56.79 62.77 58.85
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 65.10 67.66 68.03 66.09 64.82 62.07 65.64 65.81 65.91 64.17 60.81 60.65 54.60 64.27 65.55 64.51 65.68 67.47 60.60 61.30 64.23 63.97 60.88 64.32 62.25
975 372 8 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 63.21 62.80 61.77 64.95 65.57 59.69 55.52 60.69 64.89 61.67 60.72 58.76 58.10 60.20 61.52 64.37 62.84 62.43 58.23 57.43 64.31 62.42 62.48 62.50 66.99
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 64.28 61.86 71.58 61.55 63.15 59.53 88.43 60.36 60.28 62.11 59.09 56.64 78.46 89.16 63.99 77.15 59.31 89.65 60.28 56.91 66.13 64.23 59.63 58.79 61.52
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 64.68 61.28 86.75 59.92 65.17 90.99 87.70 59.97 61.21 43.72 89.96 91.36 61.07 85.39 58.60 56.47 60.74 58.89 90.94 56.03 61.17 60.22 61.84 54.98 61.23
1036 372 8 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 78.76 61.66 59.88 59.80 60.57 56.68 86.29 61.12 43.72 53.56 54.76 58.11 58.89 58.31 59.37 91.86 54.81 91.09 56.92 57.51 58.45 61.72 60.11 59.77 57.38
1039 372 8 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 55.62 63.42 87.85 61.10 87.49 59.55 62.84 58.74 61.71 62.20 58.10 57.57 62.31 61.98 58.59 88.74 60.54 86.85 91.83 57.09 81.30 62.08 59.01 60.09 59.99
1088 372 8 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 89.21 61.29 88.37 61.99 62.29 59.43 56.03 60.52 90.47 43.72 59.18 58.93 89.93 91.33 43.72 62.26 43.72 60.94 59.01 58.01 57.96 60.18 59.41 60.52 60.11
1091 372 8 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 88.33 60.52 89.77 61.74 61.74 58.55 61.49 60.21 59.13 90.22 59.93 57.09 91.08 59.88 60.86 91.96 59.19 58.68 55.27 55.86 62.23 63.99 59.63 50.32 59.19
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 87.45 64.13 62.34 62.60 63.56 91.34 89.45 62.28 60.89 60.11 59.25 59.21 92.45 60.30 61.26 89.90 60.64 60.42 92.11 86.69 59.35 59.96 56.95 59.66 49.04
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 63.03 89.71 63.72 61.20 62.54 91.95 87.41 60.60 61.47 89.72 55.37 60.25 88.48 60.93 60.43 90.67 59.64 59.23 93.43 58.25 56.40 58.01 58.74 59.47 59.23
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 68.04 65.12 62.78 62.22 66.18 59.08 54.79 65.32 67.11 66.64 61.77 59.17 65.81 69.12 63.05 58.04 64.07 65.58 48.36 60.58 65.49 65.53 67.19 65.33 65.35
1155 372 8 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 83.84 58.72 60.58 60.97 61.02 85.43 55.48 59.37 54.47 88.76 61.50 57.39 58.91 58.22 57.21 45.27 58.32 55.76 57.88 79.73 63.01 66.43 59.82 56.64 62.51
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 68.03 61.94 66.68 63.39 64.62 62.24 56.91 64.55 66.55 64.90 61.15 60.15 65.30 62.63 65.09 64.77 65.28 80.75 60.78 58.40 62.09 64.49 65.55 68.00 68.40
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 64.64 62.97 56.50 61.78 61.13 62.02 65.05 61.36 63.12 64.09 60.48 61.79 87.10 60.02 65.79 63.95 61.57 62.27 59.01 59.03 64.07 62.37 63.88 63.00 62.98
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 63.27 61.16 63.40 63.89 63.04 59.41 87.71 61.60 60.34 60.50 88.77 57.82 90.37 60.21 61.32 61.61 62.34 62.51 83.91 88.91 64.41 61.35 62.58 66.01 62.19
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.66 88.44 62.31 61.67 60.50 90.84 87.20 63.42 89.36 62.82 86.75 90.70 56.03 60.84 60.66 84.42 59.35 61.33 59.03 59.83 63.82 61.67 60.31 63.62 59.40
1228 372 8 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 55.22 62.51 57.19 62.87 86.02 90.21 61.55 63.38 62.06 68.35 57.20 60.12 69.76 60.10 61.73 89.82 62.26 58.29 56.28 57.34 60.79 62.32 60.43 58.66 60.60
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 88.83 62.54 62.13 61.70 60.89 91.50 62.33 60.16 62.73 62.42 91.21 60.65 92.54 83.02 62.51 91.30 60.34 61.52 60.32 57.10 60.30 62.47 62.05 61.14 60.31
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 89.24 60.81 61.86 90.37 88.42 91.56 88.44 60.67 61.58 62.84 61.71 59.01 90.91 59.66 59.41 91.21 58.11 59.22 57.80 58.32 60.55 56.03 60.52 59.43 60.06
1283 372 8 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 55.01 62.48 60.66 60.22 86.25 57.11 90.22 60.94 83.22 59.48 56.40 87.88 91.58 57.84 60.40 59.84 59.09 57.22 58.02 57.54 57.78 55.85 56.04 58.01 57.99
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 88.20 61.53 88.59 60.81 60.97 85.56 61.04 59.29 90.47 90.77 86.43 57.82 83.30 58.59 58.88 58.46 57.77 90.28 87.58 56.33 58.26 57.19 55.73 57.33 57.50
1295 372 8 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 62.34 63.77 61.30 60.57 89.71 90.78 82.91 60.25 88.36 61.22 59.57 58.89 90.76 57.74 60.37 90.94 60.71 62.41 58.86 58.52 61.65 63.82 50.42 59.06 56.62
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 71.39 70.84 68.74 72.69 65.30 66.23 52.13 70.63 69.59 69.62 63.59 62.70 67.55 66.27 66.65 53.07 69.81 67.78 43.72 65.17 70.13 69.81 66.47 66.03 70.97
1347 372 8 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 58.03 63.17 61.47 63.16 63.09 60.96 56.91 60.62 64.26 63.49 62.16 58.47 88.36 61.63 62.15 57.33 58.90 59.63 60.51 57.81 63.55 60.41 53.26 66.94 62.28
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 65.97 66.98 63.13 64.24 63.31 61.58 86.68 55.07 66.03 64.81 61.48 60.32 63.91 63.17 64.95 63.63 63.87 64.10 60.55 60.26 69.01 67.68 63.21 66.64 63.31
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 65.93 63.97 62.80 64.96 65.91 56.07 55.57 65.26 87.18 64.97 60.02 60.39 56.84 64.63 63.03 63.34 63.20 64.10 61.48 59.69 66.77 68.82 62.23 64.56 64.68
1408 372 8 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 62.90 61.88 87.63 62.35 58.77 88.62 56.75 60.89 59.87 59.27 59.34 57.65 88.67 56.66 59.29 60.56 59.38 58.28 58.53 55.63 62.14 63.61 61.14 59.60 59.63
1411 372 8 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 60.94 55.95 62.75 58.21 88.28 58.27 88.97 59.57 57.61 60.83 90.78 57.05 55.88 57.14 58.43 88.13 55.69 90.53 59.27 57.86 61.78 60.87 63.52 59.12 60.03
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 57.91 63.17 64.46 64.01 63.21 90.04 66.62 65.11 62.63 61.18 59.39 60.85 89.39 90.74 62.02 60.22 62.09 62.39 59.10 58.94 61.44 61.37 61.12 68.22 59.79
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 63.53 62.26 62.03 88.78 60.23 61.44 64.88 60.90 62.50 63.05 89.47 60.47 91.03 61.18 61.54 61.97 61.07 60.87 90.18 58.54 62.23 61.35 62.99 60.80 57.90
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 88.47 61.01 86.16 61.49 62.09 60.60 86.46 60.27 90.22 62.21 59.92 56.31 92.51 59.82 59.89 58.92 59.55 91.67 58.66 90.47 64.71 55.74 59.63 61.16 59.37
1475 372 8 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 87.97 61.39 87.45 60.96 60.47 59.45 62.04 59.51 61.07 88.99 90.81 59.30 91.43 60.36 60.28 58.45 60.05 58.41 57.83 56.59 57.89 59.67 56.56 57.91 59.79
1484 372 8 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 90.19 61.56 61.79 61.22 62.60 56.78 50.38 60.90 62.77 90.04 91.37 60.04 89.72 59.84 58.61 60.06 58.93 59.32 89.66 57.92 62.67 60.60 58.53 58.04 58.91
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 87.47 64.43 89.80 62.19 89.22 58.85 88.69 59.06 90.67 62.82 92.31 60.10 60.73 60.69 60.02 45.81 61.11 90.60 59.90 56.88 89.43 58.11 57.67 58.24 58.60
1536 372 8 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 45.90 62.56 63.05 64.01 62.10 61.12 49.74 62.39 65.03 64.89 62.12 43.72 60.47 61.61 54.73 63.19 65.29 54.90 59.28 56.56 68.98 64.81 65.18 66.11 62.32
1539 372 8 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 56.64 59.26 64.68 60.21 56.30 58.48 85.71 57.72 54.84 62.56 60.94 55.98 87.48 59.37 63.68 58.30 64.03 62.16 57.06 56.53 62.60 61.17 62.23 61.77 58.32
1548 372 8 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 64.36 63.72 65.04 62.34 66.80 56.95 68.39 61.14 57.16 86.27 54.80 61.08 63.35 62.98 60.26 60.19 59.96 55.50 58.79 56.44 62.83 60.23 62.79 66.89 60.24
1551 372 8 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 63.86 63.61 65.06 64.44 65.30 57.81 57.61 63.63 62.57 63.62 56.11 59.44 58.04 62.13 63.22 55.54 60.51 64.70 58.95 61.29 65.80 65.78 64.75 67.60 59.14


input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
0 372 8 0.1 16 0.00100 24 0.000000e+00 0.000000e+00 60.67 60.61 60.96 60.07 53.06 58.94 59.40 59.31 63.04 60.85 60.50 58.46 64.07 63.09 60.37 62.88 61.42 59.96 59.06 59.27 61.20 62.72 62.66 61.76 59.99
3 372 8 0.1 16 0.00100 24 0.000000e+00 1.000000e-08 49.82 58.05 59.20 59.52 59.30 60.40 61.02 60.05 60.38 60.51 58.24 58.40 61.22 49.91 59.66 48.12 59.87 62.29 60.77 57.58 61.30 61.74 63.03 61.17 62.83
12 372 8 0.1 16 0.00100 24 1.000000e-08 0.000000e+00 50.55 48.12 60.45 58.59 58.15 60.20 48.55 60.57 60.72 51.90 48.12 60.85 60.53 60.21 59.11 60.74 61.01 57.99 60.80 57.36 62.23 48.12 61.35 60.78 62.39
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 60.25 58.62 60.35 60.99 59.26 60.33 49.61 48.88 60.28 60.67 60.22 58.65 61.05 58.88 59.94 59.17 60.63 59.96 59.96 59.63 61.82 61.43 61.69 61.15 60.55
64 372 8 0.1 32 0.00100 24 0.000000e+00 0.000000e+00 51.78 48.12 57.82 61.53 61.00 49.35 58.06 59.80 60.24 59.88 60.02 61.65 59.18 49.70 58.85 60.74 60.11 61.06 58.25 58.00 60.52 61.02 62.15 62.04 62.87
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 56.80 61.84 57.16 61.15 61.08 48.12 63.56 60.06 58.39 60.68 55.46 60.97 60.51 60.13 59.78 57.69 59.59 57.67 58.96 59.85 61.95 61.83 62.96 62.88 61.44
76 372 8 0.1 32 0.00100 24 1.000000e-08 0.000000e+00 60.97 59.58 61.08 58.04 60.60 59.52 57.26 59.52 48.12 56.81 62.29 50.54 86.80 60.97 60.80 57.42 60.06 59.56 49.26 59.32 61.27 62.83 63.37 61.39 61.24
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 59.05 62.10 55.96 60.60 60.28 59.32 59.52 60.16 57.15 60.28 59.88 62.70 87.16 60.08 48.12 60.37 59.74 60.08 60.77 61.29 60.79 62.25 62.69 62.20 61.63
128 372 8 0.1 64 0.00100 24 0.000000e+00 0.000000e+00 61.88 62.45 60.22 61.65 60.20 57.74 60.39 61.90 59.22 61.99 61.31 60.15 58.05 60.85 60.96 59.43 61.17 60.93 60.82 60.90 61.66 61.72 62.84 62.19 62.60
131 372 8 0.1 64 0.00100 24 0.000000e+00 1.000000e-08 59.61 62.50 58.24 60.50 60.37 60.86 57.79 51.39 50.06 50.00 60.77 61.65 59.63 61.85 61.23 60.85 60.72 57.88 61.31 51.06 62.44 61.83 62.34 62.18 62.40
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 59.00 61.40 61.28 61.15 59.77 59.80 59.23 60.44 60.77 82.94 49.80 60.17 59.73 61.43 61.99 48.32 58.81 61.99 61.25 61.15 61.60 61.82 59.63 61.39 62.45
143 372 8 0.1 64 0.00100 24 1.000000e-08 1.000000e-08 62.47 61.82 61.81 59.12 61.64 62.38 58.41 60.93 60.67 61.46 59.77 61.99 58.89 60.88 60.88 50.37 60.78 58.54 48.12 61.93 62.24 62.34 61.89 62.37 62.13
192 372 8 0.1 16 0.00100 36 0.000000e+00 0.000000e+00 48.96 60.53 49.93 60.50 60.36 58.40 55.12 61.58 49.67 61.16 57.98 58.14 64.76 60.40 59.24 61.34 60.11 59.90 59.56 57.66 60.99 63.39 62.09 60.92 59.59
195 372 8 0.1 16 0.00100 36 0.000000e+00 1.000000e-08 57.87 58.88 59.12 58.02 56.72 58.32 56.48 58.58 58.66 58.69 59.44 58.75 57.53 57.53 58.69 58.17 55.62 59.63 58.74 58.64 61.61 62.23 60.60 60.71 61.79
204 372 8 0.1 16 0.00100 36 1.000000e-08 0.000000e+00 60.32 48.61 60.64 59.38 61.07 60.99 48.12 60.07 59.16 60.48 50.65 48.12 49.65 57.21 61.02 48.12 60.65 59.66 59.73 58.80 60.99 64.15 62.29 61.66 60.84
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 60.28 60.98 59.21 60.77 60.90 60.15 59.43 61.04 60.33 60.30 60.48 60.70 60.91 60.93 60.23 57.42 58.95 60.43 60.18 59.77 61.30 59.53 60.69 61.06 60.09
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 57.17 61.06 58.92 61.99 60.47 60.84 57.91 62.25 61.19 58.02 62.79 59.37 57.89 60.58 60.81 59.02 60.95 50.61 60.48 59.35 62.25 62.78 62.95 63.48 62.10
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 61.16 60.37 61.37 60.34 61.22 59.25 57.47 61.44 57.71 59.51 57.43 61.43 61.23 49.19 60.82 75.41 59.66 61.18 60.09 59.57 61.78 62.14 61.94 45.25 61.80
268 372 8 0.1 32 0.00100 36 1.000000e-08 0.000000e+00 49.88 60.93 50.29 59.93 59.04 59.78 48.12 61.40 61.53 60.03 57.60 59.74 58.83 60.48 60.79 59.38 61.01 60.59 59.97 58.16 61.25 60.41 61.74 62.05 60.95
271 372 8 0.1 32 0.00100 36 1.000000e-08 1.000000e-08 56.15 60.80 61.67 59.02 59.42 57.73 48.12 59.83 61.02 58.63 59.33 61.14 57.35 60.68 60.34 57.59 60.75 62.30 59.20 61.25 62.19 62.17 61.60 61.72 60.56
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 57.74 61.29 61.62 61.93 60.77 60.06 56.64 61.70 58.40 61.11 61.19 48.12 58.59 60.72 60.79 58.82 60.57 58.51 61.65 61.36 61.91 61.68 62.26 62.51 62.12
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 57.83 61.81 59.17 61.87 60.13 56.31 58.72 61.65 60.51 60.54 61.59 61.65 59.34 60.10 61.59 59.49 60.88 57.91 58.61 60.58 61.90 62.05 61.66 61.73 61.84
332 372 8 0.1 64 0.00100 36 1.000000e-08 0.000000e+00 61.32 61.59 61.29 61.59 50.26 62.32 58.89 59.82 91.95 60.55 60.77 59.56 50.67 61.94 60.77 60.50 61.93 58.51 60.77 61.98 62.43 62.48 61.53 62.87 62.68
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 57.96 61.45 61.17 61.87 59.53 60.65 58.88 62.13 58.08 58.25 61.59 61.25 85.74 61.29 60.83 59.02 60.02 50.06 60.74 59.62 61.72 61.51 63.37 61.99 61.93
384 372 8 0.1 16 0.00100 48 0.000000e+00 0.000000e+00 48.12 58.36 60.24 60.15 58.92 59.13 57.33 59.19 59.99 59.21 59.21 59.24 60.57 53.04 58.85 60.43 60.52 62.17 56.33 58.98 62.79 61.98 62.01 63.69 61.68
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 60.28 60.99 49.50 59.37 50.61 48.12 49.46 35.10 60.22 60.64 59.80 59.42 57.88 58.88 60.57 62.76 59.64 59.94 58.54 59.67 61.56 60.81 60.91 60.39 62.57
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 59.09 60.25 61.54 60.60 59.90 48.56 50.43 59.49 59.00 59.19 58.53 59.02 46.16 59.23 59.25 58.64 60.31 60.21 58.66 58.28 61.54 62.59 61.58 60.78 61.88
399 372 8 0.1 16 0.00100 48 1.000000e-08 1.000000e-08 55.81 58.75 58.97 50.26 61.71 48.84 48.07 51.67 57.46 58.61 59.64 59.73 57.37 60.88 60.15 59.20 58.42 56.23 50.08 58.75 60.85 59.92 61.82 60.96 61.24
448 372 8 0.1 32 0.00100 48 0.000000e+00 0.000000e+00 49.74 60.70 59.27 59.49 60.95 58.21 57.43 61.39 59.76 58.22 57.52 60.47 57.69 60.39 60.02 57.40 60.75 61.28 60.48 59.54 62.63 60.89 61.77 61.92 61.06
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 57.49 60.41 60.37 61.26 57.29 61.01 59.19 59.88 60.64 60.63 60.94 60.24 57.44 60.33 60.83 50.08 60.34 57.60 59.32 51.34 61.52 59.82 61.81 61.51 62.18
460 372 8 0.1 32 0.00100 48 1.000000e-08 0.000000e+00 61.24 60.14 67.49 62.06 61.15 60.17 59.28 60.46 60.77 61.35 60.08 60.33 58.07 60.76 60.17 49.51 59.84 58.92 61.99 60.67 61.79 60.20 62.55 62.57 61.80
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 57.99 60.64 60.62 62.36 60.89 58.51 57.33 60.08 58.88 60.71 61.62 58.61 48.12 59.93 60.71 59.52 61.02 60.08 61.09 59.38 62.26 62.76 60.03 62.28 61.94
512 372 8 0.1 64 0.00100 48 0.000000e+00 0.000000e+00 57.84 58.74 61.53 61.64 61.40 58.30 61.26 61.53 59.63 60.74 61.59 61.18 48.12 60.75 60.93 86.47 60.97 61.11 61.31 61.41 63.02 61.69 61.39 62.30 61.43
515 372 8 0.1 64 0.00100 48 0.000000e+00 1.000000e-08 61.58 61.66 49.59 61.66 61.40 60.22 57.99 61.70 58.21 60.99 62.70 50.25 50.77 61.16 62.00 50.56 60.63 61.39 61.37 59.62 61.63 61.86 62.67 63.04 62.29
524 372 8 0.1 64 0.00100 48 1.000000e-08 0.000000e+00 56.61 60.61 61.38 61.71 61.18 56.17 58.35 61.65 59.67 61.29 58.86 59.92 61.45 61.66 61.36 77.89 60.82 58.98 59.67 59.66 62.40 62.16 61.83 61.65 60.93
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 59.57 61.65 62.06 61.97 61.93 60.21 57.26 61.17 59.84 90.67 61.93 61.84 59.44 62.08 61.88 50.58 60.67 62.08 61.56 60.65 60.46 62.85 62.18 62.57 62.59
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 60.44 61.24 59.49 60.16 61.74 60.65 47.45 59.84 59.88 59.75 59.42 59.23 59.25 65.29 60.63 57.96 59.14 58.87 59.39 59.35 61.48 60.57 60.60 61.10 60.83
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 48.60 60.56 59.58 61.16 59.34 60.09 59.36 60.90 49.45 61.40 60.48 59.54 61.29 59.47 59.97 58.57 60.46 59.23 60.17 59.31 60.95 61.78 60.88 60.74 61.93
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 56.41 62.26 59.97 59.18 58.01 59.13 60.52 59.74 58.56 59.96 59.80 61.50 59.41 59.37 60.85 60.52 59.27 59.80 60.03 58.47 60.93 62.67 62.80 62.53 62.48
591 372 8 0.1 16 0.00010 24 1.000000e-08 1.000000e-08 59.50 59.41 59.55 60.24 59.07 48.12 48.41 59.04 60.19 59.17 61.13 58.81 61.37 59.84 58.91 61.47 50.41 59.79 60.61 59.42 61.88 48.12 48.12 62.39 62.19
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 57.99 60.21 59.58 61.01 57.73 60.32 58.03 59.93 61.73 58.42 59.64 58.67 58.51 60.82 60.33 59.90 60.56 60.29 59.71 60.40 61.68 62.04 62.68 61.52 61.60
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 61.36 60.82 61.13 61.09 61.63 59.74 58.58 61.39 48.12 60.83 60.42 60.58 60.42 60.41 59.95 57.77 60.18 82.77 60.06 60.17 60.98 61.57 61.66 62.07 61.23
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 56.36 61.68 60.05 61.44 60.10 57.62 56.24 61.40 58.61 61.16 59.15 61.47 58.97 60.51 61.25 60.77 60.48 60.37 61.59 59.21 62.44 61.45 61.79 61.78 61.82
655 372 8 0.1 32 0.00010 24 1.000000e-08 1.000000e-08 60.40 62.65 61.22 62.00 61.82 48.12 61.47 60.20 61.09 60.62 61.52 61.66 57.44 60.59 61.80 60.62 60.08 59.48 59.88 61.15 61.62 61.27 60.53 62.37 61.60
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 61.16 61.87 61.27 59.81 61.93 60.11 59.64 61.76 60.67 61.39 60.33 62.39 48.50 60.90 61.75 59.43 61.49 59.45 62.97 59.04 60.33 62.55 62.32 62.42 61.84
707 372 8 0.1 64 0.00010 24 0.000000e+00 1.000000e-08 60.22 60.66 61.89 61.29 57.85 61.99 59.09 62.06 48.88 62.32 60.77 61.77 59.21 61.36 61.54 59.68 60.98 61.75 61.47 61.81 62.45 62.79 62.81 62.79 62.19
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 59.45 61.99 61.92 48.12 59.52 60.28 58.03 61.82 49.18 58.63 61.99 62.00 59.42 61.82 60.75 51.35 61.10 60.51 61.65 59.06 59.87 62.26 61.49 62.49 61.76
719 372 8 0.1 64 0.00010 24 1.000000e-08 1.000000e-08 61.05 59.74 49.49 61.03 60.12 60.38 58.25 60.54 59.85 61.46 49.75 61.99 59.20 60.18 61.51 60.74 60.85 59.52 61.64 88.98 62.50 62.36 61.50 62.00 61.18
768 372 8 0.1 16 0.00010 36 0.000000e+00 0.000000e+00 58.30 60.70 59.26 58.29 50.69 59.58 51.02 48.12 58.40 61.07 58.42 58.50 48.12 61.08 60.50 59.86 66.09 62.36 57.21 57.74 61.19 62.29 61.48 62.96 62.60
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 60.65 60.53 59.46 60.30 59.33 59.11 58.86 59.18 59.91 58.47 60.42 58.42 57.63 59.61 60.41 59.84 59.15 58.18 58.54 58.78 61.00 62.26 62.76 61.68 61.80
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 59.99 60.00 60.11 59.55 58.38 58.81 51.02 61.32 59.51 60.53 60.17 59.44 60.04 59.38 60.91 59.38 59.46 59.86 59.16 59.99 62.31 60.74 61.60 61.28 62.15
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 60.49 59.77 59.33 60.97 60.61 59.39 59.78 60.49 58.70 60.10 59.75 59.84 59.18 60.14 59.75 60.20 58.83 59.11 58.84 58.61 60.36 61.40 60.32 61.73 60.09
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 60.48 61.67 58.67 59.36 60.96 60.98 58.86 60.32 53.08 61.37 47.75 61.53 60.41 60.57 60.37 59.78 60.35 60.99 62.40 57.79 61.06 62.22 62.17 61.79 62.62
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 58.08 61.37 58.97 58.38 60.80 62.20 58.41 89.37 56.44 61.50 58.89 59.20 58.43 60.99 60.41 59.68 59.93 58.89 60.31 60.53 61.24 62.19 62.16 61.55 60.72
844 372 8 0.1 32 0.00010 36 1.000000e-08 0.000000e+00 49.52 60.31 50.47 59.82 60.21 59.41 47.21 61.57 61.39 60.96 58.51 59.61 57.60 61.12 60.53 55.99 57.83 61.08 61.84 60.56 61.91 60.11 62.32 61.67 61.08
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 58.93 57.38 60.72 58.88 60.38 60.76 56.87 61.05 48.86 61.25 59.16 60.53 58.98 60.47 60.42 59.65 59.80 61.07 58.03 60.54 62.27 60.86 60.80 61.32 60.75
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 58.90 61.42 61.01 62.00 59.72 90.60 57.93 61.20 48.12 49.79 61.53 60.11 57.97 61.67 61.07 59.29 62.18 61.67 61.25 59.15 61.79 62.50 62.00 62.89 62.17
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 55.40 61.76 59.07 59.73 61.54 59.14 59.78 62.11 62.00 60.96 59.71 61.04 59.04 61.46 62.34 56.88 61.58 58.35 61.65 58.99 60.92 62.45 62.07 62.63 62.41
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 57.79 59.56 61.55 60.44 58.19 59.95 51.41 62.00 61.36 59.18 51.55 51.80 60.01 61.70 62.25 59.73 61.00 61.46 88.06 59.06 61.43 61.60 61.47 62.61 62.49
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.57 62.00 59.06 59.52 59.22 61.90 59.49 60.91 59.36 62.32 60.22 59.95 59.91 58.42 62.28 59.05 60.03 59.22 62.90 60.65 61.57 62.05 62.09 48.62 62.01
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 60.69 58.84 48.99 60.55 60.04 59.87 61.04 58.84 60.07 50.32 51.19 60.31 59.53 60.13 59.48 59.73 62.96 58.44 59.54 59.23 61.64 62.09 62.32 67.63 61.05
963 372 8 0.1 16 0.00010 48 0.000000e+00 1.000000e-08 59.83 61.16 59.35 60.53 58.33 58.73 59.24 58.37 57.54 60.46 59.76 60.91 60.62 59.45 58.99 59.79 58.12 60.17 59.75 58.81 60.54 58.56 61.16 62.61 61.56
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 59.24 59.36 60.87 61.00 60.42 59.96 61.00 64.32 60.18 59.34 59.26 58.99 52.63 59.28 61.29 58.31 59.16 59.37 60.65 60.05 61.28 61.99 62.95 60.19 61.50
975 372 8 0.1 16 0.00010 48 1.000000e-08 1.000000e-08 59.52 59.23 58.49 59.84 60.71 58.79 49.29 59.67 58.27 59.23 60.22 58.57 48.01 59.49 59.33 60.23 62.34 59.70 58.66 58.88 62.07 61.43 61.84 62.19 60.56
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 61.08 61.25 62.54 59.50 61.44 62.71 57.80 58.81 60.15 60.77 60.37 50.57 47.44 58.54 57.86 75.80 58.64 56.80 60.82 58.25 61.70 60.98 62.49 62.74 61.97
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 60.25 59.98 58.51 60.25 60.75 59.67 58.80 59.26 58.90 48.12 50.01 59.15 59.59 47.95 60.58 49.59 60.47 60.88 58.70 59.34 60.63 62.16 60.18 62.50 61.10
1036 372 8 0.1 32 0.00010 48 1.000000e-08 0.000000e+00 87.56 60.87 60.22 60.93 58.87 58.76 50.13 58.99 48.12 64.74 51.45 60.22 59.64 61.28 60.48 57.85 50.78 56.76 60.44 60.06 61.63 62.23 61.83 62.20 60.54
1039 372 8 0.1 32 0.00010 48 1.000000e-08 1.000000e-08 50.29 61.89 57.17 60.76 57.43 61.04 60.64 60.24 60.21 60.23 59.18 60.52 59.69 60.47 61.51 57.43 60.94 85.72 58.88 60.60 85.90 62.23 62.47 61.79 61.56
1088 372 8 0.1 64 0.00010 48 0.000000e+00 0.000000e+00 58.72 60.17 58.89 61.71 61.64 61.61 49.90 61.99 58.61 48.12 61.99 61.53 58.92 60.02 48.12 61.46 48.12 61.77 61.99 61.15 62.48 62.06 62.45 62.75 61.15
1091 372 8 0.1 64 0.00010 48 0.000000e+00 1.000000e-08 58.45 59.52 58.63 60.77 62.30 60.59 61.25 61.29 61.14 58.85 62.39 61.31 58.87 60.85 61.91 58.47 60.49 61.40 50.00 59.57 60.04 61.91 60.91 50.49 62.19
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.69 61.55 60.87 61.31 60.72 59.48 58.97 61.70 61.51 61.44 61.85 61.58 59.52 61.41 61.70 57.64 60.82 62.09 59.37 52.38 62.90 62.33 62.30 62.56 46.00
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 61.88 59.48 61.29 60.75 61.99 58.62 59.27 61.15 60.92 59.12 59.17 61.99 60.19 60.59 60.40 59.33 61.36 60.98 59.95 61.87 62.46 62.69 62.56 62.08 62.24
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 59.73 59.62 62.79 61.30 60.03 58.65 52.91 60.43 61.35 61.33 59.69 59.64 61.78 58.81 61.14 64.98 60.50 59.73 45.06 58.91 61.75 61.18 61.35 61.42 61.80
1155 372 8 0.1 16 0.00001 24 0.000000e+00 1.000000e-08 55.40 60.02 59.56 59.93 60.82 56.22 50.21 58.47 50.72 57.07 59.82 58.91 61.75 59.51 59.05 44.27 59.55 49.24 59.70 85.86 61.99 60.59 62.71 62.84 59.09
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 60.26 59.06 60.26 59.35 59.11 59.30 49.40 59.68 58.74 58.74 60.43 59.14 61.41 61.28 59.82 59.72 60.46 59.21 60.37 57.95 62.32 59.23 62.12 60.46 60.80
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 59.63 60.48 50.31 61.49 60.60 59.64 61.77 59.36 61.15 60.84 60.79 59.54 58.83 59.18 61.36 59.91 60.02 59.35 59.65 60.15 60.02 61.32 61.47 61.44 61.43
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 60.29 58.88 58.32 59.47 60.96 58.90 58.26 59.61 58.79 60.37 51.35 59.47 58.42 58.62 59.09 61.54 60.81 62.28 87.22 56.55 61.69 61.39 61.60 61.30 61.64
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 58.28 59.36 61.75 60.38 60.75 59.40 58.88 61.50 58.12 61.65 50.99 59.48 50.25 60.09 60.45 52.21 60.78 59.77 59.47 61.65 61.61 62.72 62.12 61.42 61.71
1228 372 8 0.1 32 0.00001 24 1.000000e-08 0.000000e+00 50.68 60.37 49.94 61.59 55.81 59.02 59.72 62.02 58.91 76.51 59.58 60.83 45.71 60.53 60.70 58.86 59.51 60.66 50.32 59.99 61.06 62.65 62.92 61.84 61.67
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 58.67 60.27 60.20 61.03 59.32 60.02 61.50 61.49 59.92 61.77 59.33 61.58 59.18 86.25 59.51 59.54 60.43 61.45 61.53 59.63 63.12 61.59 62.25 61.80 62.13
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 59.53 61.03 61.86 60.14 59.80 59.26 59.30 62.09 60.34 61.14 61.59 61.99 59.24 61.18 60.86 58.80 60.32 61.80 60.11 61.11 63.47 62.84 62.53 62.18 61.89
1283 372 8 0.1 64 0.00001 24 0.000000e+00 1.000000e-08 50.25 60.97 60.71 61.29 58.23 59.37 59.32 61.70 87.81 61.66 60.97 50.82 59.55 61.47 61.93 61.64 60.74 60.07 62.17 61.76 62.08 62.60 62.78 61.61 61.21
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 59.39 61.99 58.51 61.33 61.43 51.74 59.62 61.93 58.40 58.62 84.92 61.70 49.68 60.50 60.58 61.39 59.85 59.62 50.60 61.87 62.20 62.14 62.58 61.96 60.89
1295 372 8 0.1 64 0.00001 24 1.000000e-08 1.000000e-08 61.10 60.69 61.93 61.81 59.71 58.51 90.46 61.70 58.97 62.08 60.64 61.82 59.23 62.39 60.97 59.27 60.07 60.14 62.64 61.68 61.42 61.55 50.01 61.84 62.16
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 58.95 58.94 61.11 58.71 61.64 57.22 49.99 59.41 59.66 60.07 58.48 57.83 60.52 60.60 61.13 51.60 59.03 61.36 48.12 57.87 59.69 60.80 61.63 61.91 62.05
1347 372 8 0.1 16 0.00001 36 0.000000e+00 1.000000e-08 47.84 61.17 59.74 59.57 60.24 59.53 49.53 59.98 60.47 59.80 61.04 57.95 57.64 60.21 60.69 51.06 59.07 62.34 60.38 50.94 62.55 63.08 44.22 59.79 62.42
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 59.76 60.13 60.04 60.33 60.05 59.82 57.98 50.93 60.43 60.33 62.12 59.57 59.23 59.48 60.05 60.79 59.29 58.64 60.51 59.19 60.72 60.68 61.87 60.68 61.53
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 59.03 61.01 60.34 60.32 61.74 49.96 49.14 59.19 56.83 59.25 62.22 60.12 49.87 59.66 59.64 60.04 59.62 59.50 59.19 59.86 60.89 59.35 61.98 61.48 60.95
1408 372 8 0.1 32 0.00001 36 0.000000e+00 0.000000e+00 61.11 60.40 56.71 60.93 60.14 57.14 49.51 60.34 60.42 61.21 59.43 59.66 58.03 50.16 59.89 60.10 61.39 62.21 60.96 50.31 61.61 61.65 62.56 61.71 62.40
1411 372 8 0.1 32 0.00001 36 0.000000e+00 1.000000e-08 59.34 49.49 59.98 59.56 59.34 60.84 58.36 61.11 58.73 59.85 56.87 60.20 50.47 59.66 58.70 57.55 50.02 57.48 61.77 60.39 61.76 61.58 60.71 60.97 61.43
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 49.86 61.27 59.20 61.63 60.02 58.28 59.78 61.16 60.09 59.62 62.13 61.93 58.32 59.24 60.30 59.66 60.67 60.68 61.03 60.44 61.77 62.32 62.36 60.26 62.34
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 61.92 61.03 61.37 57.94 60.93 61.45 60.20 60.77 61.42 61.28 55.56 61.59 58.63 61.31 60.53 60.24 60.29 60.38 57.35 61.53 60.75 62.25 62.13 61.45 60.95
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 58.88 62.32 56.55 60.97 61.41 60.92 88.69 61.11 57.61 60.22 62.32 59.93 58.31 62.18 61.58 60.71 60.72 58.94 60.46 50.83 60.35 49.51 62.36 62.52 61.00
1475 372 8 0.1 64 0.00001 36 0.000000e+00 1.000000e-08 59.15 61.47 59.52 61.06 61.29 61.68 61.33 61.11 61.59 59.17 60.01 62.26 59.32 62.15 61.94 61.23 61.26 59.76 61.16 61.34 62.42 61.83 62.55 61.26 61.53
1484 372 8 0.1 64 0.00001 36 1.000000e-08 0.000000e+00 59.31 59.92 61.75 60.00 61.02 49.75 51.94 61.93 61.53 59.40 57.43 61.65 59.15 61.21 60.51 58.24 60.23 60.93 52.20 60.44 61.80 61.74 62.13 61.53 62.27
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.75 61.52 59.26 62.32 59.41 62.08 58.77 61.93 59.10 61.42 59.79 62.18 62.16 61.21 61.42 65.45 60.41 59.48 61.53 59.45 60.03 60.46 61.95 61.82 62.40
1536 372 8 0.1 16 0.00001 48 0.000000e+00 0.000000e+00 65.84 60.54 59.99 59.36 60.32 59.22 52.83 61.08 60.87 58.17 60.09 48.12 61.69 61.30 52.11 59.40 59.83 50.01 59.34 58.54 60.46 61.26 61.42 61.46 61.22
1539 372 8 0.1 16 0.00001 48 0.000000e+00 1.000000e-08 50.50 58.35 60.99 58.59 49.86 60.13 56.52 58.89 51.01 59.44 58.07 59.70 57.61 60.24 60.41 57.80 59.25 59.87 59.47 58.33 62.27 60.61 62.36 62.18 61.90
1548 372 8 0.1 16 0.00001 48 1.000000e-08 0.000000e+00 59.36 59.74 59.79 59.97 60.43 59.43 60.07 59.30 49.20 56.81 51.47 60.60 59.62 58.59 62.46 61.96 58.23 50.17 59.85 50.13 62.85 62.31 62.58 60.38 62.83
1551 372 8 0.1 16 0.00001 48 1.000000e-08 1.000000e-08 60.89 60.25 58.55 60.59 59.81 57.87 49.67 59.64 59.16 58.89 49.99 60.11 49.19 61.63 60.43 51.26 60.26 59.44 59.76 60.01 61.33 61.11 61.75 60.74 62.78
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues = []
pvalues_real = []

for _,index in enumerate(dt_valid_sub.index):
  _, p_value = stats.ttest_ind(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')
  pvalues_real.append(p_value)
  pvalues.append((p_value >= 0.05)*1)

  

dt_valid_sub['pvalues'] = pvalues_real
dt_valid_sub['sig'] = pvalues


dt_valid_sub1 = dt_valid_sub.query('sig == 1')


max_indexx = dt_valid_sub1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.66 88.44 62.31 61.67 60.50 90.84 87.20 63.42 89.36 62.82 86.75 90.70 56.03 60.84 60.66 84.42 59.35 61.33 59.03 59.83 63.82 61.67 60.31 63.62 59.40
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 88.83 62.54 62.13 61.70 60.89 91.50 62.33 60.16 62.73 62.42 91.21 60.65 92.54 83.02 62.51 91.30 60.34 61.52 60.32 57.10 60.30 62.47 62.05 61.14 60.31
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 87.47 62.41 89.51 89.18 63.39 61.01 89.56 83.26 86.89 61.55 91.82 56.69 90.18 60.20 58.71 61.22 59.00 58.02 56.86 58.98 60.75 58.11 60.39 59.49 57.66
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 64.68 61.28 86.75 59.92 65.17 90.99 87.70 59.97 61.21 43.72 89.96 91.36 61.07 85.39 58.60 56.47 60.74 58.89 90.94 56.03 61.17 60.22 61.84 54.98 61.23
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 85.92 62.52 86.84 61.52 60.48 43.72 56.28 61.21 87.16 64.16 88.25 58.68 61.32 58.74 59.05 89.89 61.15 87.99 92.21 56.04 60.29 60.23 59.11 59.73 59.51
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 88.42 62.49 86.25 61.84 61.35 92.42 88.26 61.40 89.55 62.08 92.09 59.67 84.68 61.43 43.72 60.59 59.85 61.00 59.26 58.30 63.92 62.27 59.44 62.05 58.68
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.20 64.05 87.63 62.79 63.92 60.11 88.10 62.45 64.07 87.34 60.39 57.83 86.95 61.27 64.63 92.24 59.32 56.39 59.77 92.46 59.18 60.61 60.90 57.16 59.91
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 88.14 62.84 61.56 60.21 88.38 58.81 89.35 88.82 61.80 61.23 59.60 58.25 89.41 59.19 60.99 55.61 59.68 89.98 58.51 87.52 63.16 61.19 60.15 58.90 60.15
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 89.24 60.81 61.86 90.37 88.42 91.56 88.44 60.67 61.58 62.84 61.71 59.01 90.91 59.66 59.41 91.21 58.11 59.22 57.80 58.32 60.55 56.03 60.52 59.43 60.06
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 88.20 61.53 88.59 60.81 60.97 85.56 61.04 59.29 90.47 90.77 86.43 57.82 83.30 58.59 58.88 58.46 57.77 90.28 87.58 56.33 58.26 57.19 55.73 57.33 57.50
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 88.47 61.01 86.16 61.49 62.09 60.60 86.46 60.27 90.22 62.21 59.92 56.31 92.51 59.82 59.89 58.92 59.55 91.67 58.66 90.47 64.71 55.74 59.63 61.16 59.37
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 87.47 64.43 89.80 62.19 89.22 58.85 88.69 59.06 90.67 62.82 92.31 60.10 60.73 60.69 60.02 45.81 61.11 90.60 59.90 56.88 89.43 58.11 57.67 58.24 58.60
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 65.16 62.53 62.79 88.89 63.26 59.18 66.61 61.00 63.52 64.26 90.78 60.05 88.79 61.57 61.30 91.71 60.66 90.47 57.54 91.96 65.10 58.98 59.80 58.59 65.50
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 88.46 62.56 63.61 43.72 88.97 90.42 87.78 60.78 84.99 89.48 60.39 57.76 89.44 57.22 59.08 85.94 59.34 60.60 57.05 92.21 87.43 58.21 58.15 60.01 59.02
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 88.57 61.95 61.41 63.75 86.41 85.71 89.53 60.79 43.72 83.37 59.06 59.69 88.95 58.75 62.96 90.56 59.49 61.76 57.81 56.14 59.05 62.53 58.91 59.20 61.40
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 85.92 61.84 89.24 88.21 61.23 57.30 88.03 61.34 60.66 60.41 56.87 57.80 91.44 59.93 61.84 89.73 57.28 91.76 58.30 93.22 58.34 57.87 60.68 59.20 58.16
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.32 89.64 64.51 60.15 88.21 91.68 84.95 59.55 61.58 89.38 87.44 88.52 89.54 57.91 60.00 91.01 57.56 61.01 83.96 54.85 59.92 58.83 59.53 58.03 56.89
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 87.15 61.02 89.21 89.40 89.51 59.47 90.29 61.72 89.72 61.05 91.42 92.42 90.91 91.60 59.14 92.11 61.52 92.24 57.28 59.07 62.80 60.77 58.26 49.09 59.96
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 87.45 64.13 62.34 62.60 63.56 91.34 89.45 62.28 60.89 60.11 59.25 59.21 92.45 60.30 61.26 89.90 60.64 60.42 92.11 86.69 59.35 59.96 56.95 59.66 49.04
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 63.03 89.71 63.72 61.20 62.54 91.95 87.41 60.60 61.47 89.72 55.37 60.25 88.48 60.93 60.43 90.67 59.64 59.23 93.43 58.25 56.40 58.01 58.74 59.47 59.23
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 89.47 61.30 61.12 61.95 87.38 90.42 88.83 61.92 60.35 81.76 88.96 57.45 91.40 60.55 60.78 88.80 92.48 60.05 58.25 58.30 56.84 62.01 89.98 59.06 57.26
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 88.35 61.23 86.23 60.61 59.33 89.55 90.24 59.74 60.41 60.76 59.04 56.87 88.98 58.23 58.85 59.00 59.01 90.92 93.15 56.00 58.99 57.60 59.09 60.54 60.10
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 88.53 59.96 60.22 61.27 89.95 58.07 90.72 60.70 90.41 90.37 58.59 60.34 82.30 57.75 59.59 91.46 60.03 55.97 57.65 55.78 59.52 61.48 55.21 58.71 59.36
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 87.89 62.31 62.06 62.19 62.80 59.24 88.41 61.47 91.55 85.14 60.77 59.33 90.96 60.50 60.55 88.10 58.87 60.20 58.57 58.00 88.60 58.49 59.77 59.62 56.70
Size of the All data:  (100, 28)
Size of the Sig data:  (24, 28)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params1 = dt_valid.loc[dt_valid_sub1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params = optimal_params1.reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
4 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 58.28 59.36 61.75 60.38 60.75 59.40 58.88 61.50 58.12 61.65 50.99 59.48 50.25 60.09 60.45 52.21 60.78 59.77 59.47 61.65 61.61 62.72 62.12 61.42 61.71
17 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 58.67 60.27 60.20 61.03 59.32 60.02 61.50 61.49 59.92 61.77 59.33 61.58 59.18 86.25 59.51 59.54 60.43 61.45 61.53 59.63 63.12 61.59 62.25 61.80 62.13
8 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 58.08 61.37 58.97 58.38 60.80 62.20 58.41 89.37 56.44 61.50 58.89 59.20 58.43 60.99 60.41 59.68 59.93 58.89 60.31 60.53 61.24 62.19 62.16 61.55 60.72
20 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 60.25 59.98 58.51 60.25 60.75 59.67 58.80 59.26 58.90 48.12 50.01 59.15 59.59 47.95 60.58 49.59 60.47 60.88 58.70 59.34 60.63 62.16 60.18 62.50 61.10
22 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 56.80 61.84 57.16 61.15 61.08 48.12 63.56 60.06 58.39 60.68 55.46 60.97 60.51 60.13 59.78 57.69 59.59 57.67 58.96 59.85 61.95 61.83 62.96 62.88 61.44
18 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 59.05 62.10 55.96 60.60 60.28 59.32 59.52 60.16 57.15 60.28 59.88 62.70 87.16 60.08 48.12 60.37 59.74 60.08 60.77 61.29 60.79 62.25 62.69 62.20 61.63
10 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 57.17 61.06 58.92 61.99 60.47 60.84 57.91 62.25 61.19 58.02 62.79 59.37 57.89 60.58 60.81 59.02 60.95 50.61 60.48 59.35 62.25 62.78 62.95 63.48 62.10
15 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 57.49 60.41 60.37 61.26 57.29 61.01 59.19 59.88 60.64 60.63 60.94 60.24 57.44 60.33 60.83 50.08 60.34 57.60 59.32 51.34 61.52 59.82 61.81 61.51 62.18
13 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 59.53 61.03 61.86 60.14 59.80 59.26 59.30 62.09 60.34 61.14 61.59 61.99 59.24 61.18 60.86 58.80 60.32 61.80 60.11 61.11 63.47 62.84 62.53 62.18 61.89
5 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 59.39 61.99 58.51 61.33 61.43 51.74 59.62 61.93 58.40 58.62 84.92 61.70 49.68 60.50 60.58 61.39 59.85 59.62 50.60 61.87 62.20 62.14 62.58 61.96 60.89
14 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 58.88 62.32 56.55 60.97 61.41 60.92 88.69 61.11 57.61 60.22 62.32 59.93 58.31 62.18 61.58 60.71 60.72 58.94 60.46 50.83 60.35 49.51 62.36 62.52 61.00
7 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.75 61.52 59.26 62.32 59.41 62.08 58.77 61.93 59.10 61.42 59.79 62.18 62.16 61.21 61.42 65.45 60.41 59.48 61.53 59.45 60.03 60.46 61.95 61.82 62.40
9 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 61.16 61.87 61.27 59.81 61.93 60.11 59.64 61.76 60.67 61.39 60.33 62.39 48.50 60.90 61.75 59.43 61.49 59.45 62.97 59.04 60.33 62.55 62.32 62.42 61.84
3 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 59.45 61.99 61.92 48.12 59.52 60.28 58.03 61.82 49.18 58.63 61.99 62.00 59.42 61.82 60.75 51.35 61.10 60.51 61.65 59.06 59.87 62.26 61.49 62.49 61.76
23 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 58.90 61.42 61.01 62.00 59.72 90.60 57.93 61.20 48.12 49.79 61.53 60.11 57.97 61.67 61.07 59.29 62.18 61.67 61.25 59.15 61.79 62.50 62.00 62.89 62.17
6 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 55.40 61.76 59.07 59.73 61.54 59.14 59.78 62.11 62.00 60.96 59.71 61.04 59.04 61.46 62.34 56.88 61.58 58.35 61.65 58.99 60.92 62.45 62.07 62.63 62.41
1 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 57.79 59.56 61.55 60.44 58.19 59.95 51.41 62.00 61.36 59.18 51.55 51.80 60.01 61.70 62.25 59.73 61.00 61.46 88.06 59.06 61.43 61.60 61.47 62.61 62.49
0 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.57 62.00 59.06 59.52 59.22 61.90 59.49 60.91 59.36 62.32 60.22 59.95 59.91 58.42 62.28 59.05 60.03 59.22 62.90 60.65 61.57 62.05 62.09 48.62 62.01
11 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.69 61.55 60.87 61.31 60.72 59.48 58.97 61.70 61.51 61.44 61.85 61.58 59.52 61.41 61.70 57.64 60.82 62.09 59.37 52.38 62.90 62.33 62.30 62.56 46.00
12 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 61.88 59.48 61.29 60.75 61.99 58.62 59.27 61.15 60.92 59.12 59.17 61.99 60.19 60.59 60.40 59.33 61.36 60.98 59.95 61.87 62.46 62.69 62.56 62.08 62.24
2 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 59.00 61.40 61.28 61.15 59.77 59.80 59.23 60.44 60.77 82.94 49.80 60.17 59.73 61.43 61.99 48.32 58.81 61.99 61.25 61.15 61.60 61.82 59.63 61.39 62.45
19 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 57.83 61.81 59.17 61.87 60.13 56.31 58.72 61.65 60.51 60.54 61.59 61.65 59.34 60.10 61.59 59.49 60.88 57.91 58.61 60.58 61.90 62.05 61.66 61.73 61.84
21 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 57.96 61.45 61.17 61.87 59.53 60.65 58.88 62.13 58.08 58.25 61.59 61.25 85.74 61.29 60.83 59.02 60.02 50.06 60.74 59.62 61.72 61.51 63.37 61.99 61.93
16 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 59.57 61.65 62.06 61.97 61.93 60.21 57.26 61.17 59.84 90.67 61.93 61.84 59.44 62.08 61.88 50.58 60.67 62.08 61.56 60.65 60.46 62.85 62.18 62.57 62.59
Size of the test data:  (24, 33)

Difference

Code
diff = dt[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt.columns,test_data_1.columns)):   
   diff[f'col_diff_{i}'] = (np.array(dt[cols[0]]) - np.array(test_data_1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff['negative_count'] = diff.apply(count_negatives, axis=1)
diff.sort_values(by =["negative_count"],inplace = True, ascending=False)

html_table = diff.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# 
# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.38 -29.08 -0.56 -1.29 0.25 -31.44 -28.32 -1.92 -31.24 -1.17 -35.76 -31.22 -5.78 -0.75 -0.21 -32.21 1.43 -1.56 0.44 1.82 -2.21 1.05 1.81 -2.20 2.31 18
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.43 -1.30 -28.24 0.33 -4.42 -31.32 -28.90 -0.71 -2.31 4.40 -39.95 -32.21 -1.48 -37.44 1.98 -6.88 -0.27 1.99 -32.24 3.31 -0.54 1.94 -1.66 7.52 -0.13 18
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.37 -0.39 -30.29 -1.24 -1.07 -33.10 -28.74 -1.24 -32.40 -1.80 -32.21 3.03 2.48 -1.35 4.40 -0.22 -0.11 -0.92 1.51 2.99 -3.13 -0.02 3.25 0.15 2.95 17
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.58 0.98 -30.15 -29.88 -30.29 2.43 -30.80 -0.81 -30.36 1.27 -31.20 -32.47 -31.00 -33.18 3.14 -33.06 -1.49 -33.02 5.62 1.58 -1.23 1.28 3.83 -0.47 2.05 16
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.00 -0.66 -1.52 -29.08 -1.33 0.93 -6.97 0.76 -2.85 -2.87 -30.45 2.34 -40.29 -0.67 0.45 -32.28 0.83 -31.02 5.43 -32.92 -4.77 3.57 2.52 3.83 -3.66 16
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.03 -2.99 -28.71 -0.80 -3.45 0.73 -30.19 -0.20 -2.88 -29.32 2.40 1.54 -29.06 -0.69 -3.82 -33.22 1.63 -5.78 0.71 -33.11 3.07 2.17 2.05 6.32 2.19 15
451 372 8 0.1 32 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.65 -2.43 -1.19 1.05 -31.09 2.20 -30.16 -28.94 -1.16 -0.60 1.34 1.99 -31.97 1.14 -0.16 -5.53 0.66 -32.38 0.81 -36.18 -1.64 -1.37 1.66 2.61 2.03 15
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.16 -2.27 -1.93 -0.67 -1.57 -31.48 -0.83 1.33 -2.81 -0.65 -31.88 0.93 -33.36 3.23 -3.00 -31.76 0.09 -0.07 1.21 2.53 2.82 -0.88 0.20 0.66 1.82 15
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.15 -30.23 -2.43 -0.45 -0.55 -33.33 -28.14 0.55 -0.55 -30.60 3.80 1.74 -28.29 -0.34 -0.03 -31.34 1.72 1.75 -33.48 3.62 6.06 4.68 3.82 2.61 3.01 14
67 372 8 0.1 32 0.00100 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.12 -0.68 -29.68 -0.37 0.60 4.40 7.28 -1.15 -28.77 -3.48 -32.79 2.29 -0.81 1.39 0.73 -32.20 -1.56 -30.32 -33.25 3.81 1.66 1.60 3.85 3.15 1.93 13
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.76 -2.58 -1.47 -1.29 -2.84 -31.86 -30.48 -0.58 0.62 1.33 2.60 2.37 -32.93 1.11 0.44 -32.26 0.18 1.67 -32.74 -34.31 3.55 2.37 5.35 2.90 -3.04 13
716 372 8 0.1 64 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.01 -0.57 -1.69 4.40 -29.45 -30.14 -29.75 1.04 -35.81 -30.85 1.60 4.24 -30.02 4.60 1.67 -34.59 1.76 -0.09 4.60 -33.15 -27.56 4.05 3.34 2.48 2.74 13
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.47 0.10 0.16 -0.80 -27.61 -30.62 -29.60 -1.48 0.42 1.18 -39.16 2.72 -31.67 0.88 1.21 -40.48 -33.67 1.94 3.00 2.85 4.76 -0.19 -30.35 2.33 5.19 12
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -32.53 -30.08 -2.96 0.29 -30.02 -31.73 -33.54 2.45 -0.22 -30.20 -35.89 -36.72 -29.53 3.79 2.25 -31.28 3.44 0.45 4.10 4.21 1.51 2.77 1.94 4.58 5.60 12
896 372 8 0.1 64 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.67 -0.53 -0.40 -1.75 -26.69 4.89 -31.60 0.41 4.40 -33.58 2.47 0.42 -30.98 2.92 -1.89 -31.27 2.69 -0.09 3.44 3.01 2.74 -0.03 3.09 3.69 0.77 12
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.72 -2.91 -30.54 0.13 -29.81 3.23 -29.92 2.87 -31.57 -1.40 -32.52 2.08 1.43 0.52 1.40 19.64 -0.70 -31.12 1.63 2.57 -29.40 2.35 4.28 3.58 3.80 11
835 372 8 0.1 32 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.39 -1.04 -30.54 -30.80 -2.59 1.19 -31.15 6.11 -30.45 -0.05 -32.93 2.51 -31.75 0.79 1.70 -1.54 0.93 0.87 3.45 1.55 0.49 4.08 1.77 2.06 3.06 11
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.59 1.31 -29.61 -0.52 -0.68 0.32 2.23 0.84 -32.61 -1.99 2.40 3.62 -34.20 2.36 1.69 1.79 1.17 -32.73 1.80 -39.64 -4.36 -6.23 2.73 1.36 1.63 11
1292 372 8 0.1 64 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.81 0.46 -30.08 0.52 0.46 -33.82 -1.42 2.64 -32.07 -32.15 -1.51 3.88 -33.62 1.91 1.70 2.93 2.08 -30.66 -36.98 5.54 3.94 4.95 6.85 4.63 3.39 10
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.71 0.22 -0.00 -30.23 -28.62 -32.30 -29.14 1.42 -1.24 -1.70 -0.12 2.98 -31.67 1.52 1.45 -32.41 2.21 2.58 2.31 2.79 2.92 6.81 2.01 2.75 1.83 10
527 372 8 0.1 64 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.32 -0.66 -0.00 -0.22 -0.87 0.97 -31.15 -0.30 -31.71 5.53 1.16 2.51 -31.52 1.58 1.33 -37.52 1.80 1.88 2.99 2.65 -28.14 4.36 2.41 2.95 5.89 10
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.52 -0.08 -30.17 -28.48 0.31 1.84 -28.25 0.77 1.34 0.55 2.84 3.24 -32.40 1.53 0.50 -32.85 4.30 -33.41 3.35 -34.23 2.58 4.58 1.39 3.43 4.25 9
323 372 8 0.1 64 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.52 0.58 -27.06 1.26 0.80 -33.24 -31.52 1.91 0.10 -0.22 2.55 4.78 -29.64 1.87 2.74 0.49 1.87 -33.01 -34.54 4.58 2.91 4.45 2.57 1.19 1.74 8
335 372 8 0.1 64 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.57 1.49 0.95 0.60 -30.42 2.58 -31.84 1.43 -32.33 -32.12 3.00 0.91 3.44 3.54 1.24 -32.44 -0.01 -5.91 3.09 3.84 2.20 0.03 8.16 3.28 2.57 8

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero 85.083333 8.102378
mAP_valid_zero_13 84.302917 11.544230
mAP_valid_zero_7 83.985833 10.433061
mAP_valid_zero_16 78.963750 16.183350
mAP_valid_zero_6 75.429167 16.893546
mAP_valid_zero_11 74.515833 15.713278
mAP_valid_zero_3 73.993750 13.070421
mAP_valid_zero_9 73.540833 15.209465
mAP_valid_zero_5 71.997083 13.128487
mAP_valid_zero_18 71.313333 15.385844
mAP_valid_zero_10 70.823750 13.858653
mAP_valid_zero_19 67.747500 15.032302
mAP_valid_zero_20 67.030417 15.581366
mAP_valid_zero_4 66.567917 12.437834
mAP_valid_zero_2 65.522083 9.230255
mAP_valid_zero_21 64.078333 9.708070
mAP_valid_zero_12 64.031667 12.279621
mAP_valid_zero_14 63.086667 9.277282
mAP_valid_zero_8 62.994583 7.218968
mAP_valid_zero_17 60.937083 6.812525
mAP_valid_zero_23 60.533750 6.490406
mAP_valid_zero_15 59.702083 3.717174
mAP_valid_zero_22 59.524167 2.030457
mAP_valid_zero_26 58.958333 2.780272
mAP_valid_zero_25 58.933750 2.699312


We then apply the hyperparameters to the test set and average the results.

Code
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_8 62.461250 5.788103
mAP_test_zero_23 62.070000 0.809852
mAP_test_zero_25 61.658333 2.826128
mAP_test_zero_10 61.636667 8.554690
mAP_test_zero_22 61.539583 2.660315
mAP_test_zero_21 61.504583 0.960570
mAP_test_zero_14 61.430833 5.968238
mAP_test_zero_19 61.341667 6.160799
mAP_test_zero_2 61.216250 0.888505
mAP_test_zero_26 61.205000 3.279959
mAP_test_zero_12 60.594167 2.168486
mAP_test_zero_15 60.573333 2.761872
mAP_test_zero_17 60.561250 0.733244
average_map 60.495000 0.834057
mAP_test_zero_6 60.484583 7.144606
mAP_test_zero_13 60.360417 8.747811
mAP_test_zero_4 60.347500 2.770020
mAP_test_zero_5 60.290833 1.183440
mAP_test_zero_7 60.115000 6.411016
mAP_test_zero_11 59.923750 6.710322
mAP_test_zero_3 59.905833 1.754772
mAP_test_zero_18 59.273333 3.101440
mAP_test_zero_20 59.101667 3.086252
mAP_test_zero 58.814167 1.396607
mAP_test_zero_9 58.688333 3.429270
mAP_test_zero_16 57.276667 4.416110
Statistical Significance:

Using the global mean maximum row as the reference, we perform the right-tailed t-test to identify significant hyperparameters.

Code
pvalues_mw = []
pvalues_real_mw = []

for _,index in enumerate(dt_valid_sub.index):

  _, p_value_mw = stats.mannwhitneyu(max_row[:-1], dt_valid_sub.loc[index][:-1], alternative='greater')#, method = 'asymptotic')
  pvalues_real_mw.append(p_value_mw)
  pvalues_mw.append((p_value_mw >= 0.05)*1)
  

dt_valid_sub_mw['pvalues_mw'] = pvalues_real_mw
dt_valid_sub_mw['sig_mw'] = pvalues_mw

dt_valid_sub_mw1 = dt_valid_sub_mw.query('sig_mw == 1')


max_indexx = dt_valid_sub_mw1.iloc[:, :-3].mean().idxmax()

#print(sum(pvalues),max_indexx)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_valid_zero mAP_valid_zero_2 mAP_valid_zero_3 mAP_valid_zero_4 mAP_valid_zero_5 mAP_valid_zero_6 mAP_valid_zero_7 mAP_valid_zero_8 mAP_valid_zero_9 mAP_valid_zero_10 mAP_valid_zero_11 mAP_valid_zero_12 mAP_valid_zero_13 mAP_valid_zero_14 mAP_valid_zero_15 mAP_valid_zero_16 mAP_valid_zero_17 mAP_valid_zero_18 mAP_valid_zero_19 mAP_valid_zero_20 mAP_valid_zero_21 mAP_valid_zero_22 mAP_valid_zero_23 mAP_valid_zero_25 mAP_valid_zero_26
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 68.04 65.12 62.78 62.22 66.18 59.08 54.79 65.32 67.11 66.64 61.77 59.17 65.81 69.12 63.05 58.04 64.07 65.58 48.36 60.58 65.49 65.53 67.19 65.33 65.35
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 68.03 61.94 66.68 63.39 64.62 62.24 56.91 64.55 66.55 64.90 61.15 60.15 65.30 62.63 65.09 64.77 65.28 80.75 60.78 58.40 62.09 64.49 65.55 68.00 68.40
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 64.64 62.97 56.50 61.78 61.13 62.02 65.05 61.36 63.12 64.09 60.48 61.79 87.10 60.02 65.79 63.95 61.57 62.27 59.01 59.03 64.07 62.37 63.88 63.00 62.98
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 71.39 70.84 68.74 72.69 65.30 66.23 52.13 70.63 69.59 69.62 63.59 62.70 67.55 66.27 66.65 53.07 69.81 67.78 43.72 65.17 70.13 69.81 66.47 66.03 70.97
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 65.97 66.98 63.13 64.24 63.31 61.58 86.68 55.07 66.03 64.81 61.48 60.32 63.91 63.17 64.95 63.63 63.87 64.10 60.55 60.26 69.01 67.68 63.21 66.64 63.31
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 65.93 63.97 62.80 64.96 65.91 56.07 55.57 65.26 87.18 64.97 60.02 60.39 56.84 64.63 63.03 63.34 63.20 64.10 61.48 59.69 66.77 68.82 62.23 64.56 64.68
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 67.51 66.81 66.12 66.51 74.73 61.66 57.16 67.62 69.41 68.02 62.68 66.25 70.24 65.14 65.76 63.59 68.62 65.56 61.68 62.39 67.30 66.41 69.03 66.25 67.93
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 58.28 62.01 65.54 65.76 61.46 60.81 64.73 61.38 59.04 64.41 59.11 59.78 62.34 59.18 64.06 64.62 64.73 61.73 60.59 59.86 66.04 64.22 64.29 67.28 62.98
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 85.53 62.01 64.33 63.83 85.90 60.27 65.88 62.63 63.15 63.80 60.50 61.18 62.77 61.20 65.79 60.62 60.07 63.47 60.67 58.51 63.57 64.35 61.92 64.46 62.49
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 64.96 61.40 61.01 64.98 64.66 59.58 63.07 62.66 64.15 61.40 60.84 59.65 87.68 62.64 62.34 63.41 62.27 61.58 57.99 59.19 64.23 63.72 62.18 66.20 66.17
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 65.52 65.53 64.55 61.45 64.51 59.20 54.21 64.36 64.08 66.78 62.93 58.25 61.61 61.76 61.80 62.59 61.05 63.72 59.31 59.69 62.18 63.18 63.13 62.75 62.09
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 66.41 64.26 63.32 64.49 64.73 61.80 66.34 64.61 64.06 62.51 59.15 59.03 64.50 62.32 63.75 67.05 65.42 63.31 59.42 57.43 67.05 63.80 67.74 65.61 67.35
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 65.91 64.19 56.86 63.70 60.83 64.22 64.98 62.42 63.36 54.32 55.39 63.42 64.12 63.08 60.96 63.25 60.98 64.39 58.98 63.46 67.42 64.95 63.46 66.85 65.81
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 65.10 67.66 68.03 66.09 64.82 62.07 65.64 65.81 65.91 64.17 60.81 60.65 54.60 64.27 65.55 64.51 65.68 67.47 60.60 61.30 64.23 63.97 60.88 64.32 62.25
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 65.42 65.02 64.94 65.93 64.71 61.95 78.06 57.81 63.08 65.07 62.43 62.91 65.24 64.06 64.44 61.44 62.85 68.90 59.89 59.04 64.92 67.46 65.79 66.72 68.90
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 67.68 68.79 68.78 67.94 67.85 66.43 69.18 64.75 66.58 64.38 67.38 63.50 67.26 64.36 66.40 71.82 69.49 66.18 65.72 63.18 64.90 71.23 67.92 68.07 68.20
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 68.43 66.34 57.79 62.97 56.31 43.72 79.09 78.38 63.47 65.84 61.40 59.78 89.08 60.16 63.19 53.95 63.36 64.43 57.12 61.72 63.84 61.40 64.75 67.49 60.03
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 67.38 63.05 66.69 66.94 65.87 59.19 56.12 63.72 66.38 64.80 57.94 65.64 59.34 86.56 61.13 65.46 64.13 66.36 60.93 66.19 65.04 64.76 62.84 67.44 64.85
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 63.27 61.16 63.40 63.89 63.04 59.41 87.71 61.60 60.34 60.50 88.77 57.82 90.37 60.21 61.32 61.61 62.34 62.51 83.91 88.91 64.41 61.35 62.58 66.01 62.19
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 88.66 88.44 62.31 61.67 60.50 90.84 87.20 63.42 89.36 62.82 86.75 90.70 56.03 60.84 60.66 84.42 59.35 61.33 59.03 59.83 63.82 61.67 60.31 63.62 59.40
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 88.83 62.54 62.13 61.70 60.89 91.50 62.33 60.16 62.73 62.42 91.21 60.65 92.54 83.02 62.51 91.30 60.34 61.52 60.32 57.10 60.30 62.47 62.05 61.14 60.31
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 57.91 63.17 64.46 64.01 63.21 90.04 66.62 65.11 62.63 61.18 59.39 60.85 89.39 90.74 62.02 60.22 62.09 62.39 59.10 58.94 61.44 61.37 61.12 68.22 59.79
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 63.53 62.26 62.03 88.78 60.23 61.44 64.88 60.90 62.50 63.05 89.47 60.47 91.03 61.18 61.54 61.97 61.07 60.87 90.18 58.54 62.23 61.35 62.99 60.80 57.90
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 86.78 62.69 64.46 62.29 88.23 59.84 60.84 59.91 63.52 90.09 91.73 57.12 91.82 60.06 59.48 60.73 60.73 63.46 57.44 58.95 63.10 62.49 59.24 63.68 62.98
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 63.25 64.65 64.14 64.25 64.17 89.06 88.04 61.65 43.72 63.50 58.71 60.17 63.52 62.82 62.86 88.07 60.38 84.08 60.33 58.54 62.77 64.09 60.70 59.95 62.66
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 86.60 64.23 61.25 61.42 60.72 90.32 86.21 59.42 88.00 61.24 90.18 59.28 90.28 59.43 62.93 60.08 61.45 58.34 59.40 57.95 59.84 62.49 58.55 60.35 61.88
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 63.11 64.16 88.09 62.34 61.70 62.14 82.78 62.95 49.83 63.49 87.38 61.40 63.37 61.57 62.46 63.79 61.97 61.47 60.05 90.75 64.82 61.42 61.32 59.75 61.13
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 88.46 86.61 61.60 60.40 63.10 59.16 85.88 60.11 55.63 62.34 90.63 58.39 90.63 61.86 60.48 62.45 60.25 63.86 91.04 58.40 61.51 59.93 60.77 61.60 59.38
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 64.28 61.86 71.58 61.55 63.15 59.53 88.43 60.36 60.28 62.11 59.09 56.64 78.46 89.16 63.99 77.15 59.31 89.65 60.28 56.91 66.13 64.23 59.63 58.79 61.52
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 64.68 61.28 86.75 59.92 65.17 90.99 87.70 59.97 61.21 43.72 89.96 91.36 61.07 85.39 58.60 56.47 60.74 58.89 90.94 56.03 61.17 60.22 61.84 54.98 61.23
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 88.42 62.49 86.25 61.84 61.35 92.42 88.26 61.40 89.55 62.08 92.09 59.67 84.68 61.43 43.72 60.59 59.85 61.00 59.26 58.30 63.92 62.27 59.44 62.05 58.68
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 86.20 64.05 87.63 62.79 63.92 60.11 88.10 62.45 64.07 87.34 60.39 57.83 86.95 61.27 64.63 92.24 59.32 56.39 59.77 92.46 59.18 60.61 60.90 57.16 59.91
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 64.49 63.22 61.79 61.09 62.59 89.97 87.92 63.02 89.38 62.12 91.86 58.58 61.06 55.48 62.05 46.71 62.76 59.58 59.86 89.58 63.15 62.28 60.32 50.80 59.49
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 89.13 62.47 61.20 62.03 62.08 58.88 87.86 61.97 89.74 62.83 60.90 55.49 43.72 59.43 61.91 91.94 63.77 60.01 57.97 56.71 61.91 57.70 88.09 61.04 60.43
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 89.24 60.81 61.86 90.37 88.42 91.56 88.44 60.67 61.58 62.84 61.71 59.01 90.91 59.66 59.41 91.21 58.11 59.22 57.80 58.32 60.55 56.03 60.52 59.43 60.06
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 88.47 61.01 86.16 61.49 62.09 60.60 86.46 60.27 90.22 62.21 59.92 56.31 92.51 59.82 59.89 58.92 59.55 91.67 58.66 90.47 64.71 55.74 59.63 61.16 59.37
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 87.47 64.43 89.80 62.19 89.22 58.85 88.69 59.06 90.67 62.82 92.31 60.10 60.73 60.69 60.02 45.81 61.11 90.60 59.90 56.88 89.43 58.11 57.67 58.24 58.60
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 65.16 62.53 62.79 88.89 63.26 59.18 66.61 61.00 63.52 64.26 90.78 60.05 88.79 61.57 61.30 91.71 60.66 90.47 57.54 91.96 65.10 58.98 59.80 58.59 65.50
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 85.92 61.84 89.24 88.21 61.23 57.30 88.03 61.34 60.66 60.41 56.87 57.80 91.44 59.93 61.84 89.73 57.28 91.76 58.30 93.22 58.34 57.87 60.68 59.20 58.16
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 90.32 89.64 64.51 60.15 88.21 91.68 84.95 59.55 61.58 89.38 87.44 88.52 89.54 57.91 60.00 91.01 57.56 61.01 83.96 54.85 59.92 58.83 59.53 58.03 56.89
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 87.15 61.02 89.21 89.40 89.51 59.47 90.29 61.72 89.72 61.05 91.42 92.42 90.91 91.60 59.14 92.11 61.52 92.24 57.28 59.07 62.80 60.77 58.26 49.09 59.96
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 87.45 64.13 62.34 62.60 63.56 91.34 89.45 62.28 60.89 60.11 59.25 59.21 92.45 60.30 61.26 89.90 60.64 60.42 92.11 86.69 59.35 59.96 56.95 59.66 49.04
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 63.03 89.71 63.72 61.20 62.54 91.95 87.41 60.60 61.47 89.72 55.37 60.25 88.48 60.93 60.43 90.67 59.64 59.23 93.43 58.25 56.40 58.01 58.74 59.47 59.23
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 89.47 61.30 61.12 61.95 87.38 90.42 88.83 61.92 60.35 81.76 88.96 57.45 91.40 60.55 60.78 88.80 92.48 60.05 58.25 58.30 56.84 62.01 89.98 59.06 57.26
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 87.94 64.65 62.17 61.04 62.46 57.04 86.61 61.29 90.47 61.19 59.23 43.72 91.18 59.52 61.15 90.43 59.74 91.46 60.84 58.32 59.05 63.77 60.16 60.63 57.86
Size of the All data:  (100, 28)
Size of the Sig data:  (45, 33)
Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params_mw1 = dt_valid.loc[dt_valid_sub_mw1.index][['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
optimal_params_mw = optimal_params_mw1.reset_index()
optimal_params_mw.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_mw1 = pd.merge(optimal_params_mw, dt_test, on=['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg'])
test_data_1_sub_mw = test_data_mw1[list(test_data_mw1.columns[test_data_mw1.columns.str.startswith('mAP_test')])]

Equivalent test data

input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg mAP_test_zero mAP_test_zero_2 mAP_test_zero_3 mAP_test_zero_4 mAP_test_zero_5 mAP_test_zero_6 mAP_test_zero_7 mAP_test_zero_8 mAP_test_zero_9 mAP_test_zero_10 mAP_test_zero_11 mAP_test_zero_12 mAP_test_zero_13 mAP_test_zero_14 mAP_test_zero_15 mAP_test_zero_16 mAP_test_zero_17 mAP_test_zero_18 mAP_test_zero_19 mAP_test_zero_20 mAP_test_zero_21 mAP_test_zero_22 mAP_test_zero_23 mAP_test_zero_25 mAP_test_zero_26
40 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 59.73 59.62 62.79 61.30 60.03 58.65 52.91 60.43 61.35 61.33 59.69 59.64 61.78 58.81 61.14 64.98 60.50 59.73 45.06 58.91 61.75 61.18 61.35 61.42 61.80
33 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 60.26 59.06 60.26 59.35 59.11 59.30 49.40 59.68 58.74 58.74 60.43 59.14 61.41 61.28 59.82 59.72 60.46 59.21 60.37 57.95 62.32 59.23 62.12 60.46 60.80
41 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 59.63 60.48 50.31 61.49 60.60 59.64 61.77 59.36 61.15 60.84 60.79 59.54 58.83 59.18 61.36 59.91 60.02 59.35 59.65 60.15 60.02 61.32 61.47 61.44 61.43
25 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 58.95 58.94 61.11 58.71 61.64 57.22 49.99 59.41 59.66 60.07 58.48 57.83 60.52 60.60 61.13 51.60 59.03 61.36 48.12 57.87 59.69 60.80 61.63 61.91 62.05
32 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 59.76 60.13 60.04 60.33 60.05 59.82 57.98 50.93 60.43 60.33 62.12 59.57 59.23 59.48 60.05 60.79 59.29 58.64 60.51 59.19 60.72 60.68 61.87 60.68 61.53
35 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 59.03 61.01 60.34 60.32 61.74 49.96 49.14 59.19 56.83 59.25 62.22 60.12 49.87 59.66 59.64 60.04 59.62 59.50 59.19 59.86 60.89 59.35 61.98 61.48 60.95
21 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 60.44 61.24 59.49 60.16 61.74 60.65 47.45 59.84 59.88 59.75 59.42 59.23 59.25 65.29 60.63 57.96 59.14 58.87 59.39 59.35 61.48 60.57 60.60 61.10 60.83
43 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 48.60 60.56 59.58 61.16 59.34 60.09 59.36 60.90 49.45 61.40 60.48 59.54 61.29 59.47 59.97 58.57 60.46 59.23 60.17 59.31 60.95 61.78 60.88 60.74 61.93
34 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 56.41 62.26 59.97 59.18 58.01 59.13 60.52 59.74 58.56 59.96 59.80 61.50 59.41 59.37 60.85 60.52 59.27 59.80 60.03 58.47 60.93 62.67 62.80 62.53 62.48
39 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 60.65 60.53 59.46 60.30 59.33 59.11 58.86 59.18 59.91 58.47 60.42 58.42 57.63 59.61 60.41 59.84 59.15 58.18 58.54 58.78 61.00 62.26 62.76 61.68 61.80
44 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 59.99 60.00 60.11 59.55 58.38 58.81 51.02 61.32 59.51 60.53 60.17 59.44 60.04 59.38 60.91 59.38 59.46 59.86 59.16 59.99 62.31 60.74 61.60 61.28 62.15
37 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 60.49 59.77 59.33 60.97 60.61 59.39 59.78 60.49 58.70 60.10 59.75 59.84 59.18 60.14 59.75 60.20 58.83 59.11 58.84 58.61 60.36 61.40 60.32 61.73 60.09
42 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 60.69 58.84 48.99 60.55 60.04 59.87 61.04 58.84 60.07 50.32 51.19 60.31 59.53 60.13 59.48 59.73 62.96 58.44 59.54 59.23 61.64 62.09 62.32 67.63 61.05
36 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 59.24 59.36 60.87 61.00 60.42 59.96 61.00 64.32 60.18 59.34 59.26 58.99 52.63 59.28 61.29 58.31 59.16 59.37 60.65 60.05 61.28 61.99 62.95 60.19 61.50
31 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 60.25 58.62 60.35 60.99 59.26 60.33 49.61 48.88 60.28 60.67 60.22 58.65 61.05 58.88 59.94 59.17 60.63 59.96 59.96 59.63 61.82 61.43 61.69 61.15 60.55
18 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 60.28 60.98 59.21 60.77 60.90 60.15 59.43 61.04 60.33 60.30 60.48 60.70 60.91 60.93 60.23 57.42 58.95 60.43 60.18 59.77 61.30 59.53 60.69 61.06 60.09
38 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 60.28 60.99 49.50 59.37 50.61 48.12 49.46 35.10 60.22 60.64 59.80 59.42 57.88 58.88 60.57 62.76 59.64 59.94 58.54 59.67 61.56 60.81 60.91 60.39 62.57
30 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 59.09 60.25 61.54 60.60 59.90 48.56 50.43 59.49 59.00 59.19 58.53 59.02 46.16 59.23 59.25 58.64 60.31 60.21 58.66 58.28 61.54 62.59 61.58 60.78 61.88
17 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 60.29 58.88 58.32 59.47 60.96 58.90 58.26 59.61 58.79 60.37 51.35 59.47 58.42 58.62 59.09 61.54 60.81 62.28 87.22 56.55 61.69 61.39 61.60 61.30 61.64
3 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 58.28 59.36 61.75 60.38 60.75 59.40 58.88 61.50 58.12 61.65 50.99 59.48 50.25 60.09 60.45 52.21 60.78 59.77 59.47 61.65 61.61 62.72 62.12 61.42 61.71
12 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 58.67 60.27 60.20 61.03 59.32 60.02 61.50 61.49 59.92 61.77 59.33 61.58 59.18 86.25 59.51 59.54 60.43 61.45 61.53 59.63 63.12 61.59 62.25 61.80 62.13
29 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 49.86 61.27 59.20 61.63 60.02 58.28 59.78 61.16 60.09 59.62 62.13 61.93 58.32 59.24 60.30 59.66 60.67 60.68 61.03 60.44 61.77 62.32 62.36 60.26 62.34
23 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 61.92 61.03 61.37 57.94 60.93 61.45 60.20 60.77 61.42 61.28 55.56 61.59 58.63 61.31 60.53 60.24 60.29 60.38 57.35 61.53 60.75 62.25 62.13 61.45 60.95
20 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 57.99 60.21 59.58 61.01 57.73 60.32 58.03 59.93 61.73 58.42 59.64 58.67 58.51 60.82 60.33 59.90 60.56 60.29 59.71 60.40 61.68 62.04 62.68 61.52 61.60
28 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 61.36 60.82 61.13 61.09 61.63 59.74 58.58 61.39 48.12 60.83 60.42 60.58 60.42 60.41 59.95 57.77 60.18 82.77 60.06 60.17 60.98 61.57 61.66 62.07 61.23
16 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 56.36 61.68 60.05 61.44 60.10 57.62 56.24 61.40 58.61 61.16 59.15 61.47 58.97 60.51 61.25 60.77 60.48 60.37 61.59 59.21 62.44 61.45 61.79 61.78 61.82
26 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 60.48 61.67 58.67 59.36 60.96 60.98 58.86 60.32 53.08 61.37 47.75 61.53 60.41 60.57 60.37 59.78 60.35 60.99 62.40 57.79 61.06 62.22 62.17 61.79 62.62
15 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 58.93 57.38 60.72 58.88 60.38 60.76 56.87 61.05 48.86 61.25 59.16 60.53 58.98 60.47 60.42 59.65 59.80 61.07 58.03 60.54 62.27 60.86 60.80 61.32 60.75
22 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 61.08 61.25 62.54 59.50 61.44 62.71 57.80 58.81 60.15 60.77 60.37 50.57 47.44 58.54 57.86 75.80 58.64 56.80 60.82 58.25 61.70 60.98 62.49 62.74 61.97
14 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 60.25 59.98 58.51 60.25 60.75 59.67 58.80 59.26 58.90 48.12 50.01 59.15 59.59 47.95 60.58 49.59 60.47 60.88 58.70 59.34 60.63 62.16 60.18 62.50 61.10
13 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 59.05 62.10 55.96 60.60 60.28 59.32 59.52 60.16 57.15 60.28 59.88 62.70 87.16 60.08 48.12 60.37 59.74 60.08 60.77 61.29 60.79 62.25 62.69 62.20 61.63
7 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 57.17 61.06 58.92 61.99 60.47 60.84 57.91 62.25 61.19 58.02 62.79 59.37 57.89 60.58 60.81 59.02 60.95 50.61 60.48 59.35 62.25 62.78 62.95 63.48 62.10
24 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 61.16 60.37 61.37 60.34 61.22 59.25 57.47 61.44 57.71 59.51 57.43 61.43 61.23 49.19 60.82 75.41 59.66 61.18 60.09 59.57 61.78 62.14 61.94 45.25 61.80
27 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 57.99 60.64 60.62 62.36 60.89 58.51 57.33 60.08 58.88 60.71 61.62 58.61 48.12 59.93 60.71 59.52 61.02 60.08 61.09 59.38 62.26 62.76 60.03 62.28 61.94
10 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 59.53 61.03 61.86 60.14 59.80 59.26 59.30 62.09 60.34 61.14 61.59 61.99 59.24 61.18 60.86 58.80 60.32 61.80 60.11 61.11 63.47 62.84 62.53 62.18 61.89
11 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 58.88 62.32 56.55 60.97 61.41 60.92 88.69 61.11 57.61 60.22 62.32 59.93 58.31 62.18 61.58 60.71 60.72 58.94 60.46 50.83 60.35 49.51 62.36 62.52 61.00
5 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 59.75 61.52 59.26 62.32 59.41 62.08 58.77 61.93 59.10 61.42 59.79 62.18 62.16 61.21 61.42 65.45 60.41 59.48 61.53 59.45 60.03 60.46 61.95 61.82 62.40
6 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 61.16 61.87 61.27 59.81 61.93 60.11 59.64 61.76 60.67 61.39 60.33 62.39 48.50 60.90 61.75 59.43 61.49 59.45 62.97 59.04 60.33 62.55 62.32 62.42 61.84
4 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 55.40 61.76 59.07 59.73 61.54 59.14 59.78 62.11 62.00 60.96 59.71 61.04 59.04 61.46 62.34 56.88 61.58 58.35 61.65 58.99 60.92 62.45 62.07 62.63 62.41
1 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 57.79 59.56 61.55 60.44 58.19 59.95 51.41 62.00 61.36 59.18 51.55 51.80 60.01 61.70 62.25 59.73 61.00 61.46 88.06 59.06 61.43 61.60 61.47 62.61 62.49
0 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 59.57 62.00 59.06 59.52 59.22 61.90 59.49 60.91 59.36 62.32 60.22 59.95 59.91 58.42 62.28 59.05 60.03 59.22 62.90 60.65 61.57 62.05 62.09 48.62 62.01
8 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 59.69 61.55 60.87 61.31 60.72 59.48 58.97 61.70 61.51 61.44 61.85 61.58 59.52 61.41 61.70 57.64 60.82 62.09 59.37 52.38 62.90 62.33 62.30 62.56 46.00
9 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 61.88 59.48 61.29 60.75 61.99 58.62 59.27 61.15 60.92 59.12 59.17 61.99 60.19 60.59 60.40 59.33 61.36 60.98 59.95 61.87 62.46 62.69 62.56 62.08 62.24
2 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 59.00 61.40 61.28 61.15 59.77 59.80 59.23 60.44 60.77 82.94 49.80 60.17 59.73 61.43 61.99 48.32 58.81 61.99 61.25 61.15 61.60 61.82 59.63 61.39 62.45
19 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 57.74 61.29 61.62 61.93 60.77 60.06 56.64 61.70 58.40 61.11 61.19 48.12 58.59 60.72 60.79 58.82 60.57 58.51 61.65 61.36 61.91 61.68 62.26 62.51 62.12
Size of the test data:  (45, 33)

Difference

Code
diff_mw = dt_mw[['input_size', 'output_size', 'learning_rate', 'batch_size', 'alpha', 'margin', 'l1_reg', 'l2_reg']]
for i, cols in enumerate(zip(dt_mw.columns,test_data_mw1.columns)):   
   diff_mw[f'col_diff_{i}'] = (np.array(dt_mw[cols[0]]) - np.array(test_data_mw1[cols[1]]))*-1

# Function to count negatives in a row
def count_negatives(row):
    return sum(1 for value in row if isinstance(value, (int, float)) and value < 0)

diff_mw['negative_count'] = diff_mw.apply(count_negatives, axis=1)

diff_mw.sort_values(by =["negative_count"],inplace = True, ascending=False)


html_table = diff_mw.to_html(index=True)

# Wrap in a scrollable div
scrollable_table = f"""
<div style="height: 400px; width: 100%; overflow-x: auto; overflow-y: auto;">
    {html_table}
</div>
"""
# Display the scrollable table
display(HTML(scrollable_table))

# show(diff)
input_size output_size learning_rate batch_size alpha margin l1_reg l2_reg col_diff_0 col_diff_1 col_diff_2 col_diff_3 col_diff_4 col_diff_5 col_diff_6 col_diff_7 col_diff_8 col_diff_9 col_diff_10 col_diff_11 col_diff_12 col_diff_13 col_diff_14 col_diff_15 col_diff_16 col_diff_17 col_diff_18 col_diff_19 col_diff_20 col_diff_21 col_diff_22 col_diff_23 col_diff_24 col_diff_25 col_diff_26 col_diff_27 col_diff_28 col_diff_29 col_diff_30 col_diff_31 col_diff_32 negative_count
207 372 8 0.1 16 0.00100 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.40 -7.81 -9.57 -7.17 -6.95 -6.28 -9.75 -3.71 -6.25 -4.08 -6.90 -2.80 -6.35 -3.43 -6.17 -14.40 -10.54 -5.75 -5.54 -3.41 -3.60 -11.70 -7.23 -7.01 -8.11 25
1164 372 8 0.1 16 0.00001 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.77 -2.88 -6.42 -4.04 -5.51 -2.94 -7.51 -4.87 -7.81 -6.16 -0.72 -1.01 -3.89 -1.35 -5.27 -5.05 -4.82 -21.54 -0.41 -0.45 0.23 -5.26 -3.43 -7.54 -7.60 24
1344 372 8 0.1 16 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -12.44 -11.90 -7.63 -13.98 -3.66 -9.01 -2.14 -11.22 -9.93 -9.55 -5.11 -4.87 -7.03 -5.67 -5.52 -1.47 -10.78 -6.42 4.40 -7.30 -10.44 -9.01 -4.84 -4.12 -8.92 24
1356 372 8 0.1 16 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -6.21 -6.85 -3.09 -3.91 -3.26 -1.76 -28.70 -4.14 -5.60 -4.48 0.64 -0.75 -4.68 -3.69 -4.90 -2.84 -4.58 -5.46 -0.04 -1.07 -8.29 -7.00 -1.34 -5.96 -1.78 24
576 372 8 0.1 16 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -7.07 -5.57 -6.63 -6.35 -12.99 -1.01 -9.71 -7.78 -9.53 -8.27 -3.26 -7.02 -10.99 0.15 -5.13 -5.63 -9.48 -6.69 -2.29 -3.04 -5.82 -5.84 -8.43 -5.15 -7.10 24
396 372 8 0.1 16 0.00100 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.29 -2.80 -5.15 -6.34 -5.97 -10.63 -5.69 -4.23 -7.38 -5.61 0.59 -6.62 -13.18 -27.33 -1.88 -6.82 -3.82 -6.15 -2.27 -7.91 -3.50 -2.17 -1.26 -6.66 -2.97 24
972 372 8 0.1 16 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.86 -8.30 -7.16 -5.09 -4.40 -2.11 -4.64 -1.49 -5.73 -4.83 -1.55 -1.66 -1.97 -4.99 -4.26 -6.20 -6.52 -8.10 0.05 -1.25 -2.95 -1.98 2.07 -4.13 -0.75 23
15 372 8 0.1 16 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.17 -6.40 -4.59 -4.94 -5.45 -1.62 -28.45 -8.93 -2.80 -4.40 -2.21 -4.26 -4.19 -5.18 -4.50 -2.27 -2.22 -8.94 0.07 0.59 -3.10 -6.03 -4.10 -5.57 -8.35 23
1359 372 8 0.1 16 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -6.90 -2.96 -2.46 -4.64 -4.17 -6.11 -6.43 -6.07 -30.35 -5.72 2.20 -0.27 -6.97 -4.97 -3.39 -3.30 -3.58 -4.60 -2.29 0.17 -5.88 -9.47 -0.25 -3.08 -3.73 23
579 372 8 0.1 16 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -9.68 -1.45 -5.96 -4.60 -2.12 -0.72 -5.37 -0.48 -9.59 -3.01 1.37 -0.24 -1.05 0.29 -4.09 -6.05 -4.27 -2.50 -0.42 -0.55 -5.09 -2.44 -3.41 -6.54 -1.05 23
771 372 8 0.1 16 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.31 -0.87 -1.55 -4.68 -5.33 -0.47 -4.21 -3.48 -4.24 -2.93 -0.42 -1.23 -30.05 -3.03 -1.93 -3.57 -3.12 -3.40 0.55 -0.41 -3.23 -1.46 0.58 -4.52 -4.37 23
1216 372 8 0.1 32 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -2.98 -2.28 -5.08 -4.42 -2.08 -0.51 -29.45 -1.99 -1.55 -0.13 -37.42 1.65 -31.95 -1.59 -2.23 -0.07 -1.53 -0.23 3.31 -32.36 -2.72 0.04 -0.98 -4.71 -0.55 22
1152 372 8 0.1 16 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.31 -5.50 0.01 -0.92 -6.15 -0.43 -1.88 -4.89 -5.76 -5.31 -2.08 0.47 -4.03 -10.31 -1.91 6.94 -3.57 -5.85 -3.30 -1.67 -3.74 -4.35 -5.84 -3.91 -3.55 22
960 372 8 0.1 16 0.00010 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.22 -5.35 -7.87 -3.15 -0.79 -4.35 -3.94 -3.58 -3.29 -4.00 -4.20 -3.11 -4.59 -2.95 -1.48 -3.52 1.98 -5.95 0.56 -4.23 -5.78 -2.86 -1.14 0.78 -4.76 22
783 372 8 0.1 16 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.92 -4.49 -3.99 -3.52 -4.12 -2.41 -6.56 -4.12 -5.36 -2.41 0.60 0.81 -5.32 -2.18 -4.00 -6.85 -6.59 -4.20 -0.58 1.18 -6.69 -2.40 -7.42 -3.88 -7.26 22
588 372 8 0.1 16 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.12 0.25 -4.36 -4.65 -27.89 -1.14 -5.36 -2.89 -4.59 -3.84 -0.70 0.32 -3.36 -1.83 -4.94 -0.10 -0.80 -3.67 -0.64 -0.04 -2.64 -1.68 0.88 -1.93 -0.01 22
1167 372 8 0.1 16 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.01 -2.49 -6.19 -0.29 -0.53 -2.38 -3.28 -2.00 -1.97 -3.25 0.31 -2.25 -28.27 -0.84 -4.43 -4.04 -1.55 -2.92 0.64 1.12 -4.05 -1.05 -2.41 -1.56 -1.55 22
387 372 8 0.1 16 0.00100 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.15 -5.35 -8.29 -3.60 -5.70 4.40 -29.63 -43.28 -3.25 -5.20 -1.60 -0.36 -31.20 -1.28 -2.62 8.81 -3.72 -4.49 1.42 -2.05 -2.28 -0.59 -3.84 -7.10 2.54 21
780 372 8 0.1 16 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -5.53 -5.53 -4.44 -1.90 -6.13 -0.39 -3.19 -3.04 -4.57 -6.25 -2.76 1.19 -1.57 -2.38 -0.89 -3.21 -1.59 -3.86 -0.15 0.30 0.13 -2.44 -1.53 -1.47 0.06 21
643 372 8 0.1 32 0.00010 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.89 -3.83 -3.01 -3.16 -2.54 -29.32 -29.46 -0.26 4.40 -2.67 1.71 0.41 -3.10 -2.41 -2.91 -30.30 -0.20 -1.31 -0.27 1.63 -1.79 -2.52 0.96 2.12 -1.43 19
1219 372 8 0.1 32 0.00001 24 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.38 -29.08 -0.56 -1.29 0.25 -31.44 -28.32 -1.92 -31.24 -1.17 -35.76 -31.22 -5.78 -0.75 -0.21 -32.21 1.43 -1.56 0.44 1.82 -2.21 1.05 1.81 -2.20 2.31 18
259 372 8 0.1 32 0.00100 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -3.33 -2.85 -0.42 -0.75 -1.37 -30.72 -30.45 -1.58 -31.67 -2.61 -34.43 2.85 0.17 -6.29 -1.23 28.70 -3.10 1.60 0.23 -30.01 -1.37 -0.14 1.62 -5.55 2.31 18
1027 372 8 0.1 32 0.00010 48 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.43 -1.30 -28.24 0.33 -4.42 -31.32 -28.90 -0.71 -2.31 4.40 -39.95 -32.21 -1.48 -37.44 1.98 -6.88 -0.27 1.99 -32.24 3.31 -0.54 1.94 -1.66 7.52 -0.13 18
1024 372 8 0.1 32 0.00010 48 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -3.20 -0.61 -9.04 -2.05 -1.71 3.18 -30.63 -1.55 -0.13 -1.34 1.28 -6.07 -31.02 -30.62 -6.13 -1.35 -0.67 -32.85 0.54 1.34 -4.43 -3.25 2.86 3.95 0.45 18
832 372 8 0.1 32 0.00010 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -2.63 -2.49 -29.42 -2.98 -0.74 -1.16 -23.92 -2.63 3.25 -2.12 -39.63 0.13 -2.96 -1.00 -2.09 -4.01 -1.62 -0.48 2.35 -32.96 -3.76 0.80 0.85 2.04 1.49 18
847 372 8 0.1 32 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.53 -29.23 -0.88 -1.52 -2.72 1.60 -29.01 0.94 -6.77 -1.09 -31.47 2.14 -31.65 -1.39 -0.06 -2.80 -0.45 -2.79 -33.01 2.14 0.76 0.93 0.03 -0.28 1.37 17
79 372 8 0.1 32 0.00100 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.37 -0.39 -30.29 -1.24 -1.07 -33.10 -28.74 -1.24 -32.40 -1.80 -32.21 3.03 2.48 -1.35 4.40 -0.22 -0.11 -0.92 1.51 2.99 -3.13 -0.02 3.25 0.15 2.95 17
1423 372 8 0.1 32 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.61 -1.23 -0.66 -30.84 0.70 0.01 -4.68 -0.13 -1.08 -1.77 -33.91 1.12 -32.40 0.13 -1.01 -1.73 -0.78 -0.49 -32.83 2.99 -1.48 0.90 -0.86 0.65 3.05 17
1420 372 8 0.1 32 0.00001 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -8.05 -1.90 -5.26 -2.38 -3.19 -31.76 -6.84 -3.95 -2.54 -1.56 2.74 1.08 -31.07 -31.50 -1.72 -0.56 -1.42 -1.71 1.93 1.50 0.33 0.95 1.24 -7.96 2.55 17
640 372 8 0.1 32 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -28.79 -2.48 -4.88 -1.28 -30.50 0.48 -2.81 0.02 -1.79 -31.67 -32.09 1.55 -33.31 0.76 0.85 -0.83 -0.17 -3.17 2.27 1.45 -1.42 -0.45 3.44 -2.16 -1.38 17
911 372 8 0.1 64 0.00010 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.58 0.98 -30.15 -29.88 -30.29 2.43 -30.80 -0.81 -30.36 1.27 -31.20 -32.47 -31.00 -33.18 3.14 -33.06 -1.49 -33.02 5.62 1.58 -1.23 1.28 3.83 -0.47 2.05 16
704 372 8 0.1 64 0.00010 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -4.00 -0.66 -1.52 -29.08 -1.33 0.93 -6.97 0.76 -2.85 -2.87 -30.45 2.34 -40.29 -0.67 0.45 -32.28 0.83 -31.02 5.43 -32.92 -4.77 3.57 2.52 3.83 -3.66 16
256 372 8 0.1 32 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.03 -2.99 -28.71 -0.80 -3.45 0.73 -30.19 -0.20 -2.88 -29.32 2.40 1.54 -29.06 -0.69 -3.82 -33.22 1.63 -5.78 0.71 -33.11 3.07 2.17 2.05 6.32 2.19 15
1231 372 8 0.1 32 0.00001 24 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.16 -2.27 -1.93 -0.67 -1.57 -31.48 -0.83 1.33 -2.81 -0.65 -31.88 0.93 -33.36 3.23 -3.00 -31.76 0.09 -0.07 1.21 2.53 2.82 -0.88 0.20 0.66 1.82 15
652 372 8 0.1 32 0.00010 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.24 -2.55 -1.20 0.02 -0.62 -32.70 -29.97 1.98 -29.39 -0.08 -31.03 2.19 -31.31 1.08 -1.68 0.69 -0.97 2.03 2.19 1.26 2.60 -1.04 3.24 1.43 -0.06 14
1103 372 8 0.1 64 0.00010 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -1.15 -30.23 -2.43 -0.45 -0.55 -33.33 -28.14 0.55 -0.55 -30.60 3.80 1.74 -28.29 -0.34 -0.03 -31.34 1.72 1.75 -33.48 3.62 6.06 4.68 3.82 2.61 3.01 14
463 372 8 0.1 32 0.00100 48 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -31.14 -1.83 -0.58 0.33 -1.19 -0.37 -30.53 -1.89 -30.86 -2.12 0.72 3.12 4.40 0.50 -1.20 -32.42 -2.75 0.07 3.12 2.67 0.35 5.06 -28.06 1.24 1.51 13
1100 372 8 0.1 64 0.00010 48 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.76 -2.58 -1.47 -1.29 -2.84 -31.86 -30.48 -0.58 0.62 1.33 2.60 2.37 -32.93 1.11 0.44 -32.26 0.18 1.67 -32.74 -34.31 3.55 2.37 5.35 2.90 -3.04 13
140 372 8 0.1 64 0.00100 24 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.47 0.10 0.16 -0.80 -27.61 -30.62 -29.60 -1.48 0.42 1.18 -39.16 2.72 -31.67 0.88 1.21 -40.48 -33.67 1.94 3.00 2.85 4.76 -0.19 -30.35 2.33 5.19 12
320 372 8 0.1 64 0.00100 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.20 -3.36 -0.55 0.89 -1.69 3.02 -29.97 0.41 -32.07 -0.08 1.96 4.40 -32.59 1.20 -0.36 -31.61 0.83 -32.95 0.81 3.04 2.86 -2.09 2.10 1.88 4.26 12
908 372 8 0.1 64 0.00010 36 1.000000e-08 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -32.53 -30.08 -2.96 0.29 -30.02 -31.73 -33.54 2.45 -0.22 -30.20 -35.89 -36.72 -29.53 3.79 2.25 -31.28 3.44 0.45 4.10 4.21 1.51 2.77 1.94 4.58 5.60 12
1472 372 8 0.1 64 0.00001 36 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.59 1.31 -29.61 -0.52 -0.68 0.32 2.23 0.84 -32.61 -1.99 2.40 3.62 -34.20 2.36 1.69 1.79 1.17 -32.73 1.80 -39.64 -4.36 -6.23 2.73 1.36 1.63 11
1487 372 8 0.1 64 0.00001 36 1.000000e-08 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -27.72 -2.91 -30.54 0.13 -29.81 3.23 -29.92 2.87 -31.57 -1.40 -32.52 2.08 1.43 0.52 1.40 19.64 -0.70 -31.12 1.63 2.57 -29.40 2.35 4.28 3.58 3.80 11
1280 372 8 0.1 64 0.00001 24 0.000000e+00 0.000000e+00 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -29.71 0.22 -0.00 -30.23 -28.62 -32.30 -29.14 1.42 -1.24 -1.70 -0.12 2.98 -31.67 1.52 1.45 -32.41 2.21 2.58 2.31 2.79 2.92 6.81 2.01 2.75 1.83 10
899 372 8 0.1 64 0.00010 36 0.000000e+00 1.000000e-08 0 0 -0.0 0 -0.0 0 -0.0 -0.0 -30.52 -0.08 -30.17 -28.48 0.31 1.84 -28.25 0.77 1.34 0.55 2.84 3.24 -32.40 1.53 0.50 -32.85 4.30 -33.41 3.35 -34.23 2.58 4.58 1.39 3.43 4.25 9

Average & Std Deviation of the Significant rows:

mean std
mAP_valid_zero_13 75.967778 14.634333
mAP_valid_zero_7 75.602667 13.243779
mAP_valid_zero 74.252222 11.498589
mAP_valid_zero_11 70.907111 14.550956
mAP_valid_zero_16 70.425556 14.419383
mAP_valid_zero_6 68.959111 14.515147
mAP_valid_zero_9 68.352667 12.177099
mAP_valid_zero_18 67.892444 11.195342
mAP_valid_zero_3 67.790667 9.876929
mAP_valid_zero_5 67.216889 9.455073
mAP_valid_zero_4 66.162889 8.540801
mAP_valid_zero_2 65.894222 7.496300
mAP_valid_zero_10 65.491333 8.828516
mAP_valid_zero_14 65.043111 9.350688
mAP_valid_zero_20 64.873778 12.273670
mAP_valid_zero_21 63.788222 4.938599
mAP_valid_zero_19 63.638889 11.703670
mAP_valid_zero_23 63.205111 6.306356
mAP_valid_zero_17 62.676889 5.343262
mAP_valid_zero_22 62.537111 3.402247
mAP_valid_zero_8 62.498667 3.567790
mAP_valid_zero_12 62.351556 9.548895
mAP_valid_zero_25 62.211111 4.397973
mAP_valid_zero_15 62.002444 3.491375
mAP_valid_zero_26 61.901111 3.980599


We then apply the hyperparameters to the test set and average the results.

Code
####################################################
# Use the hyperparameters to the test data.
####################################################
optimal_params = dt_valid.loc[dt_valid_sub_mw1.index].iloc[:, :6].reset_index()
optimal_params.drop(['index'], axis=1, inplace = True)

#rotation invariance test data with optimal parameters
test_data_1 = pd.merge(optimal_params, dt_test, how='left')
test_data_1_sub = test_data_1[list(test_data_1.columns[test_data_1.columns.str.startswith('mAP_test')])]
test_data_1['average_map'] = test_data_1_sub.apply(np.mean, axis=1)

test_data_1.sort_values(by=['average_map'], ascending= False,inplace=True)
mean std
mAP_test_zero_21 61.795056 2.670702
mAP_test_zero_26 61.448556 1.796655
mAP_test_zero_25 61.323111 2.849762
mAP_test_zero_23 61.305333 3.059522
mAP_test_zero_22 61.210056 2.535423
mAP_test_zero_18 60.359333 4.610879
mAP_test_zero_15 60.297889 1.840798
mAP_test_zero_14 60.259056 4.319369
mAP_test_zero_4 60.229444 1.728561
mAP_test_zero_2 60.215222 2.214090
mAP_test_zero_8 60.044722 4.867475
mAP_test_zero_10 59.973889 3.985827
mAP_test_zero_19 59.941278 6.292059
average_map 59.808222 0.963510
mAP_test_zero_17 59.781222 2.591528
mAP_test_zero_5 59.730944 2.200121
mAP_test_zero_20 59.698278 4.701437
mAP_test_zero_12 59.669333 2.440527
mAP_test_zero_3 59.146278 3.201553
mAP_test_zero_11 59.037444 3.876609
mAP_test_zero_6 58.992722 5.486129
mAP_test_zero_16 58.885889 4.457514
mAP_test_zero_9 58.767722 4.992287
mAP_test_zero_13 58.290500 5.490554
mAP_test_zero 58.211833 4.837632
mAP_test_zero_7 56.590444 6.297457


Summary using radar plot

Code
res1_valid['id'] = res1_valid.index.to_series().apply(extract_number)
res1_test['id'] = res1_test.index.to_series().apply(extract_number)



res_comb = pd.concat([res1_valid,res1_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res1_test = res1_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range1 = np.array(list(res1_valid['mean']) + list(res1_test['mean']))

categories = [str(i) for i in range(1,26)]

fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res1_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res1_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "T-Test",
        'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range1.min()), round(data_range1.max()) + 1]
    )),
  showlegend=True
)

fig.show()




##############


res2_valid['id'] = res2_valid.index.to_series().apply(extract_number)
res2_test['id'] = res2_test.index.to_series().apply(extract_number)


res_comb = pd.concat([res2_valid,res2_test])
index_series = res_comb.index.to_series()

res_comb['type'] = np.where(
    index_series.str.contains('valid', case=False), 'valid',
    np.where(index_series.str.contains('test', case=False), 'test', 'unknown')
)
res_comb = res_comb.query("type !='unknown'")

res_comb =  res_comb.reset_index(drop=True)


res2_test = res2_test.sort_values(by=['id']).reset_index().query("index !='average_map'")

data_range2 = np.array(list(res2_valid['mean']) + list(res2_test['mean']))

categories = [str(i) for i in range(1,26)]
fig = go.Figure()

# Valid
fig.add_trace(go.Scatterpolar(
       r=list(res2_test['mean']),
      theta=categories,
      #fill='toself',
      name='Test'
))

# Test
fig.add_trace(go.Scatterpolar(
      r=list(res2_valid['mean']),
      theta=categories,
      #fill='toself',
      name='Valid'
))

# Customization of chart
fig.update_layout(
  title={
      'text': "MU-Test",
         'xanchor': 'center',
      'yanchor': 'top'
  },
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[round(data_range2.min()), round(data_range2.max()) + 1]
    )),
  showlegend=True
)

fig.show()

best_valid_bit_size_8 = round(res1_valid['mean'][0])
id_best_valid = res1_valid['id'][0]
best_test_bit_size_8 = list(round(res1_test.query('id == @id_best_valid')['mean'],2))[0]

best_valid_bit_size_8_mw = round(res2_valid['mean'][0])
id_best_valid = res2_valid['id'][0]
best_test_bit_size_8_mw = list(round(res2_test.query('id == @id_best_valid')['mean'],2))[0]




Comparisons of bit size results

T-test curves

MU-test curves